ORGANIZATIONAL ANTECEDENTS TO THE IMPLEMENTATION OF PRECISION MEDICINE: OVERCOMING RESISTANCE TO CHANGE
A Dissertation Submitted to the Temple University Graduate Board In Partial Fulfillment of the Requirements for the Degree
EXECUTIVE DOCTORATE IN BUSINESS ADMINISTRATION
by
Stephen Michael Sammut
Diploma Date: August 2020
Examining Committee Members
Professor Ram Mudambi, Committee Chair, Frank M. Speakman Professor of Strategy and Perelman Senior Research Fellow in Strategic Management at the Fox School of Business and Management at Temple University
Professor Susan Mudambi, Committee Member, Associate Professor of Marketing and Director Executive Doctorate in Business Administration Program, Fox School of Business, Temple University
Professor T.L. Hill, Committee Member, Associate Professor in Strategic Management and Managing Director of the Fox Management Consulting Practice, Fox School of Business, Temple University
Professor Lynne Andersson, External Reader, Associate Professor, Department of Human Resource Management, Fox School of Business, Temple University
Organizational Antecedents to the Implementation of Precision Medicine: Overcoming Resistance to Change.
© Copyright 2020, Stephen M. Sammut. All Rights Reserved.
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ABSTRACT
Precision medicine (PM) is “the treatment and prevention of disease that takes into
account individual variability in genes, environment, and lifestyle for each person” (NIH,
2015). PM was poised to transform clinical practice in 2003 when the Human Genome
Project reached completion but resistance to implementation at virtually all health care
providers provides the basis for novel study on the diffusion of innovation as well as
operational strategy. Existing studies on resistance to PM explore the role of reimbursement, economics, regulatory affairs, and public policies. Investigation into the antecedent conditions for implementation at the physician and organizational levels has been overlooked, a gap this study fills. The research captures the reasons for resistance at
the physician and organizational levels and identifies operational strategies for successful implementation at three health care institutions with fully integrated PM programs. The
research produced 42 findings with managerial implications and six testable propositions
for future research. The dynamics of resistance to PM has revealed key implications for theories of organizational change. These include the observation that the formulation processes of clinical standards of practice in PM are not predicted by prevailing organizational theory; that conventional theories of resistance to change do not fully anticipate the effects of Kuhnian level historic paradigm shifts; and, that communities of practice play a critical role in transformational clinical change. Further, the research
demonstrated that PM implementation is characterizable through reproducible
organizational and cultural actions; that positive clinical outcomes are measurable and
persuasive; and that the needs of stakeholders can be reconciled by aligning physician
standards of practice with patient expectations and organizational needs.
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DEDICATION
To my parents, Marie and Paul, for their triumph over many dangers, toils, and snares in the least precise ways but always with amazing grace.
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ACKNOWLEDGEMENTS
Taking on doctoral studies late in life probably should not be on many bucket lists, but it was on mine. I begin these acknowledgements going back fifty years to my undergraduate time at Villanova University as a humanities with sciences major. It was there that the boundaries between philosophy and biology first crumbled and cross- disciplinary learning became my touchstone for determining truth. Throughout my studies and intellectual growth those disciplines that resisted reductionism and thrived on complexity led me down the long path to the completion of this work. My undergraduate professors’ admonitions not to take anything for granted still echo with me. Professors
Michael Slattery, John McClain, and Richard O’Brien (who introduced me to the concept of the paradigm shift) have long shed this mortal coil but the unity of knowledge they espoused endures for me. Dedication to excellence was also instilled in me by the three transplant surgeons who trusted me with forming and managing the regional organ transplant program in Philadelphia in my early twenties: the late Drs. Aaron Bannett
(Albert Einstein Medical Center) and Robert Bower (Hahnemann Medical College), and
Dr. Clyde Barker (University of Pennsylvania). They confronted me with the first professional fork in my career and through them I learned that medicine could succeed despite its imprecision if it is practiced with unrelenting devotion to excellence. I hope that my work has lived up to their standards.
The process of transitioning my all too practical entrepreneurial and financial life to this adventure in research was encouraged by my colleagues on the Wharton faculty, in particular, Professors Lawton Burns, Mauro Guillen and Mark Pauly. They have long been role models for me, and their support made a massive difference in my choice to
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pursue and survive this journey. Of course, my advisors at the Fox School of Temple
University provided guidance and patience as this research progressed through several
iterations and arrived ultimately at its long overdue end point. Professor Ram Mudambi
undoubtedly found my wandering frustrating, but he gently guided me on to more fruitful
tracks and challenged my methodology incessantly. As I fumbled initially with a domain
for this research, Professor TL Hill started me on the path of addressing the industry I
know best as the topic arena for this research, and Professor Susan Mudambi, the director
of the doctoral program, in addition to providing unending guidance on my research strategy also bent more than a few rules on my behalf. Finally, Professor Lynne
Andersson offered her time as an external reader. To all, I am grateful.
The extensive interviews at the three institutions profiled but left anonymous at
their request are the heart of the research and shared insights. The hospitality and time
that my hosts and their colleagues invested in this research are warmly regarded with my enduring gratitude. I hope that sharing their perspective of precision medicine through the lens of this study will serve to further evangelize other health care providers of this important paradigm shift – an ethos that the three institutions share.
Finally, my children, Paul and Andrea, who have never quite figured out their
dad, cheered me on even though these academic efforts stole from our precious time
together. This doctoral diversion from my other tasks in global health development and
health care management education delayed my further immersion into vital projects. I
now must make up for lost time. I can only hope that this work in some small manner
accelerates the arrival of precision medicine for the benefit of all who have helped me
along the way.
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REFLECTIONS
The understatement:
“It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material.”
James Watson & Francis Crick “Molecular Structure of Nucleic Acids” Nature, April 25, 1953
The cynical reality:
“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.” Max Planck Scientific Autobiography, 1950
The problem and the cure:
“Health care today is in crisis as it is expensive, reactive, inefficient, and focused largely on one-size-fits all treatments for events of late stage disease. An answer is personalized, predictive, preventive and participatory medicine.”
Ralph Snyderman, MD Chancellor Emeritus, Duke University James B. Duke Professor of Medicine Executive Director, Duke Center for Personalized Health Care Founder, Proventys
The revelation:
"This is not a big deal. This is just a revolution."
Dr. Liisa-Maria Voipio-Pulkki Director General, Chief Medical Officer Ministry of Social Affairs and Health Finland The challenge: “Hey buddy, can you paradigm?”
John L. Casti Paradigms Lost, 1989
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TABLE OF CONTENTS
Page ABSTRACT ……………………………………………………………………………..iii
ACKNOWLEDGEMENTS ………………………………………………………………v
KEY WORDS …………………………………………………………………………..xiii
LIST OF TABLES ……………………………………………………………………...xiv
LIST OF FIGURES……………………………………………………………………..xvi
PREFACE..…………………………………………………………………………….xviii
CHAPTER
1: INTRODUCTION TO THE DISSERTATION……………………………………...…1
Precision Medicine in the Biopharmaceutical Industry: a Paradigm Shift …………………………………………………………..1
Application of the Structure of Scientific Revolutions to the Life Sciences ………..2
Criteria for the Determination of a Paradigm Shift ………………………………13
The Convergence of the Pharmaceutical and Biotechnology Industries: Role in the Paradigm Shift ……………………………………………… 14
The Arguments of this Study ………………………………………………...... 17
Definition and Settings…………………………………………………………...18 Essential Definitions of Pharmaceutical Commerce and Therapeutics
Motivation and Impact of Research ……………………………………………...24
A MAP THROUGH CHAPTERS 2 AND 3: OUTLINE, CONTENT AND THRUST...30
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2 (STUDY 1): THE PATH TO PRECISION MEDICINE
Introduction ……………………………………………………………………39
Research Questions …………………………………………………………...…41
Theoretical Framing ……………………………………………………………..42
Practical Framing ………………………………………………………………..44
Literature Review ………………………………………………………………..49
Precision Medicine Evolution …………………………………………………...54 Dueling Business Models Impact in Pharmaceutical Development The Producer Dimension Historical Capsule of Medicinal Discovery A Conceptual Model The Rise of Precision Medicine Theoretical and Managerial Challenges Convergence of Forces Scientific, Clinical, and Demographic Factors Commercial Forces Social Forces 1980 as the Pivot Year
Foundational Thinking for the Antecedent Conditions and Consequences ………83 Factors Suggesting a Paradigm Shift Why and How organizations Resist Characterizing the Obstacles to Implementation of Precision Medicine
Revisiting the Arguments ………………………………………………………100
Research Questions, Methodology and Data Sources ………………………….101 Methodology
Data Presentation and Analysis ………………………………………………...104 Framing Argument One Use and Abuse of “Paradigm Shifts” in Describing Medical Change Factors Influencing and Signaling a Paradigm Shift How Precision Medicine Challenges Producers and Stakeholders The Economics of a Paradigm Shift Institutional Theory Applied to Precision Medicine Adoption
Evidence for Argument One ……………………………………………………115 The Crisis Precipitating the Paradigm Shift Page ix | 477
Demonstration of Argument One QED: Precision Medicine is a Kuhnian Paradigm Shift
Does the Literature Support the Conclusion? …………………………………...122
Framing Argument Two: Status and Readiness…………………………………126
Evidence Supporting Argument Two…………………………………………...128 Profile of Approved Medicines Profile of Companion Diagnostics Profile of Global Development Pipelines Economic Considerations in the Adoption of Precision Medicine Precision Medicine Development in a Global Context
QED: Precision Medicine as a Paradigm Shift Invites Resistance ……………...144
A Conclusion of Study 1: Evidence for a Paradigm Shift ……………………….146
Is There Resistance to the Normal Science of the Molecular Period? …………148
Summary of Conclusions of Study 1..…………………………………………..152
Transition from Study 1 to Study 2 …………………………………………….154
3 (STUDY 2): AN EXPLORATION OF PROVIDER ORGANIZATIONAL AND DECISION DYNAMIC READINESS FOR PRECISION MEDICINE IN THE UNITED STATES
Introduction to Study 2: Paradigm Shifts and Resistance to Change in Scientific and Medical Practice ……………………………...156
Study 2 Objectives: The Significance of this Research …………………………159
Literature Reviews: Theory Addressing Resistance to Change ………………...166 Defining the Concept of Change: Organizations vs Communities of Practice Do Communities of Practice Function Similarly to Organizations in Matters of Change? General Organizational Theory on Resistance to Change Health Care Organizational Theory Addressing Resistance to Change
Approach to Formation and Exploration of Research Questions ……………….215
Basis for Selection of the Institutions Alpha, Beta and Gamma ……………….216
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Research Questions, Methodology and Data Sources for Study 2 ……………..217 Methodology
Analytic Framework for Interview Data ………………………………………..225
Interview Themes and Questions ……………………………………………….228
Conducting the Interviews ……………………………………………………...232
Driving Towards Interpretation and Conclusions ………………………………234
Derivation of Interview Themes and Nodes ……………………………………235
Interviews: Summary of Findings and Derivation of Propositions …….………240
Discussion and Conclusions from Interview Findings …………………………265 Restatement of Arguments and Research Questions
Grounded Theory Families and the Cascade of Issues …………………………266
The Findings, Propositions, and their Implications ……………………………..270
Congruity of Findings with Organizational Literature on Change ……………..279
Incongruity of Findings with Organizational Literature on Change.……………283
Do the Peculiarities of Implementing Precision Medicine Inform the Organizational Literature on Resistance to Change? …………………...290
4: CONCLUSIONS
Synthesis of Studies 1 and 2: Lessons from the Research……………………...294
Limitations of the Study ………………………………………………………..296
Opportunities for Additional Research…………………………………………299
REFERENCES CITED ………………………………………………………………...303
APPENDICES
A: IRB REVIEW……..………………………………………………………...345
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B: CURRENTLY APPROVED PRECISION MEDICINES WITH BIOMARKERS………………………………………………………...346
C: COMPENDIUM OF COMPANION DIAGNOSTICS IN DEVELOPMENT………………………………………………………351
D: GLOBAL DEVELOPMENT PIPELINE OF PRECISION MEDICINES AND COMPANION DIAGNOSTICS ………………………………..363
E: INTERVIEW GUIDE (MASTER) …………………………………………380
F: SUMMARY OF INTERVIEWS BY CODING CATEGORY, NODES AND THEMES………………………………………………..383
G: GLOSSARY OF SCIENTIFIC AND CLINICAL TERMS..……………….450 (Terms in the text appearing in Bold Italics are defined in Appendix G)
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KEY WORDS
Precision medicine
Personalized medicine
Individualized medicine
Companion diagnostics
Patient centricity
Evidenced based medicine
Paradigm shift
Kuhn
Organizational theory
Change management
Resistance to change
Grounded theory
Genomics
Pharmacogenomics
Pharmacoeconomics
Electronic Health Records (EHR)
Biobanks
Bioethics
Communities of practice
Guilds
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LIST OF TABLES Table 1: Author’s conception and delineation of Kuhnian level paradigm shifts in the life sciences and medicine ………………………………………..9
Table 2: Principal stakeholders in precision medicine…………………………………..19 Table 3: Representative examples of publications by category …………………………50 Table 4: Reconfiguration of antecedents and consequences in the era of precision medicine. Author’s formulation……………………………...... 86
Table 5: Contrasting traditional and precision care...……………………………………90
Table 6: Implications for re-thinking business plans and models associated with precision medicine. ………………………………………………...... 93 Table 7: Response rates of patients to a major drug for a selected group of therapeutics areas …………………………………………………………….116
Table 8: Precision Medicine’s Status in Cancer Care. Percentage of patients whose tumors are driven by certain genetic mutations that could be targets for specific therapeutics, by types of cancer……………………..117
Table 9: Summary of Approved Precision Medicines by medical specialty. See Appendix B for details ………………………………………………… 132
Table 10: Breakdown of companion diagnostics in development by disease targets ……………………………………………………………………...... 133
Table 11: Breakdown of precision medicines in development by disease targets.………135 Table 12. Worldwide Market Potential for Precision Medicine in (US $ millions) by 2020 ……………………………………………………………...144
Table 13: The Four Theoretical Lenses and their Indicators ……………………………192
Table 14: Sources of resistance to change in the strategy formulation stage……………206
Table 15: Sources of resistance to change in the implementation stage………………...207
Table 16: Simple rules for the design of the 21st century health care systems…………. 208
Table 17: Relationship of Coding Categories, Nodes, and Themes Explored in the Interviews ……………………………………………………………...230
Table 18: Professional functions of the 50 interviewees at Institutions Alpha, Beta and Gamma………………………………………………………………..232
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Table 19: Precision Medicine Pilot Project Matrix ……….………………………….. 236
Table 20, Part A: Process Flow for Development of a Precision Medicine Program and Clinical Management Strategy……………………………….. 237
Table 20, Part B: Stage Two: Developmental activities and organizational readiness ………………………………………………………………. 238
Table 20, Part C: Stage Three: Clinical implementation……………………………… 239
Table 21: Potentials for growth, sustainability, and integration as a standard of practice ………………………………………………………………. 240
Table 22: Relationship of Coding Categories, Nodes, and Themes Explored in the Interviews ……………………………………………………………. 244
Table 23: Relationship of the Propositions to supporting the Arguments or answering the Research Questions of Study 2 ………………………………………... 268
Table 24: Comparison of precision medicine related factors at the three institutions….271 Table 25: Universal applicability of selected Group 2 and 4 Findings in Table 23 for the derivation of Propositions …………………………………………………….. 273
Table 26: Universal applicability of selected Group 1 and 5 Findings in Table 23 for the derivation of Propositions ……………………………………………………...275
Table 27: Universal applicability of selected Group 3 and 6 Findings in Table 23 for the derivation of Propositions………………………………………………………277
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LIST OF FIGURES
Figure 1: Author’s summary of periods and phases of pharmaceutical history (in Figures 2, 3, and 5) …………………………………………57
Figure 2: First or “Serendipity Period” of pharmaceutical discovery and industrial development. Source: ……………………………..……………………...59
Figure 3: The second period, “Suggestive Rational Design,” of pharmaceutical discovery and development characterized by growing sophistication in chemistry married to greater insight into the underlying biology of disease allowing more specific chemical structures to engage with disease targets.………………………………………60
Figure 4: The pharmaceutical industry value chain, inputs and outputs during phases one and two of the industry’s history.……………………………61
Figure 5: The third period, “Molecular/Genomic,” ushered in the biopharmaceutical industry and drove development and the transition of targeted molecular specificity of a pharmaceutical to genomically driven precision medicine.……………………………………………....63
Figure 6. Conceptual model illustrating the passage of therapeutic interventions from a broadcast business model through to a narrowcast model and ultimately a precision paradigm mediated by technological forces but resisted by organizational and professional inertia.……………………………………………....69
Figure 7: The regulatory backdrop for precision medicine.………………………………80
Figure 8: Dynamics of antecedent – consequent reconsiderations for precision medicine…………………..……………………………………………..…84
Figure 9: The stakeholder universe of precision medicine – a simplification of Table 2 in the Introduction…………………………………………..88
Figure 10: Drivers of precision medicine. ……………………….………………………89
Figure 11: Brave new world of integrating knowledge categories to the care planning and business model process………………………………………...91
Figure 12. From a linear product-centered to a patient-centric business model to illustrate business model impact of precision medicine……………...92
Figure 13: Progress of precision medicine and the interrelationship of milestones and issues. ………………………………………….……………………137
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Figure 14: The Kuhn Cycle as derived from a reading of Kuhn………………………. 150
Figure 15: Antecedents, explicit reactions and change consequences of organizational change. ……………………………………………………………… 194
Figure 16: Relationship between utility of precision medicine with disease state: organizational capabilities and therapeutic realities……………………………………278
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PREFACE
This research studies how the rapidly emerging clinical field built on molecular principles, better known as precision medicine or “the treatment and prevention of disease that takes into account individual variability in genes, environment, and lifestyle for each person” (NIH, 2015), represents a paradigm shift in medical care (Study 1). The exploration also studies antecedent conditions necessary for implementing precision medicine. Moreover, the nature of resistance to adoption of principles and practices of precision medicine shows incongruities with prevailing organizational theory (Study 2).
Chapter 2 (Study 1) presents five research questions: 1) Is the practice of medicine undergoing a paradigm shift towards precision medicine? 2) What is the status of precision medicine therapeutic offerings? 3) What is the status of precision medicine diagnostic offerings? 4) What are the regulatory, economic, and commercial realities of precision medicine? 5) If conditions indicate that precision medicine is a paradigm shift, what are the implications for organizational policies and professional practice?
In preparation for this research, informal preliminary discussions, interviews, and public forums held over a one-year period revealed a surfeit of professional opinion sometimes unsupported by accumulated and analyzed evidence. These publications, discussion groups and conferences focused on the rate of precision medicine adoption and recounted clinical and policy issues. They did not describe the organizational dynamics of the provider organizations, the misalignment of business models, physician concerns, or the lack of a coherent approach to the development of standards of practice for precision medicine – missing pieces that this dissertation addresses.
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To answer the research questions, the research methodology of Study 1 has two
components: 1) historiography of medical paradigm shifts and circumstances leading to
precision medicine and, 2) quantitative analysis of product offerings and their clinical
applications. The ensuing arguments of Study 1 are that:
• precision medicine represents a Kuhnian paradigm shift in health care;
• resistance to precision medicine is resistance to a clinical mindset derived
from the paradigm shift to molecular medicine in the mid-20th century;
• there are determinable and manageable reasons for this resistance.
The capability for implementation of precision medicine is currently in place by
virtue of the approved products on the market and those in the global development pipeline.
Moreover, further development of regulatory frameworks and favorable economic
evaluation has trended positively towards supporting precision medicine, although some
issues remain to be resolved. Despite that readiness and the urgency for adoption, the
clinical establishment of precision medicine is lagging because the organizational
antecedents for implementation have been insufficiently incorporated into systems planning.
Resistance in embracing a true paradigm shift by the physician community of practice
contributes to the lag in implementation. There are at least three health care provider
institutions in the United States that have fully integrated operational precision medicine
programs; there are potential lessons from their success.
Findings of Study 1 provoked three research questions for Chapter 3 (Study 2):
• Research Question One: Foundational concerns – What are the antecedent
conditions for precision medicine to be incorporated into strategies for care
delivery and guidelines for professional practice?
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• Research Question Two: Provider readiness – How is precision medicine
positioned operationally to be incorporated into patient care based on
cultures and systems established at exemplary institutions?
• Research Question 3: Change dynamics – What are the implications of the
pace of adoption of the precision medicine paradigm at the exemplary
institutions for the field of organization theory, in particular, its subfield of
resistance to change?
In order to address these questions, Study 2 pursues a qualitative, semi-structured interview-driven investigation within the inductive Grounded Theory framework.
Grounded Theory drives interview findings to be formulated into testable propositions for future investigation. The framework probes thought patterns among the interviewees through language analysis and coding. Three of the leading health care institutions in America in precision medicine were identified and approached for intensive on-site interviewing. Fifty health care professionals participated in 37 interviews over a combined two-week period while the author was embedded in the precision medicine programs at their institutions.
The scholarly output of Study 2 interprets the arguments made by interviewees regarding the following: processes in clinical decision making at organizational levels; the machinery of standards of practice development; the basis for individual physician decision processes; and, the associated value judgements of each of these categories.
The interviews produced 42 Findings which were re-formulated into three groups of
Propositions that define successful implementation of a precision medicine program. The interpretation of arguments made in the interviews also strongly suggests new insights for
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the theoretical literature on organizational change, especially as related to decisions made by
physicians within an organizational clinical context. Specifically, when physicians resist change it is a function of professional communities of practice that are driven by evidence-
backed standards of practice, not by organizational dictates. The role of “communities of practice” in resistance to a paradigm shift is largely neglected in the literature. As applied to medicine, the profession of medicine at large is a community of practice. More to the point, however, the Board of Medical Examiners’ certification of specialties creates the operant communities of practice which individually reach scientific and clinical consensus on new approaches to diagnosis, intervention, and patient care. Each specialty has its own criteria for determining what can be embraced as legitimate practice in accordance with standards of behavior, decision making and acceptable clinical outcomes, i.e., standards of care.
There is deliberate asymmetry in the design of Studies 1 and 2. Specifically, this manuscript’s approach to resistance to precision medicine and successful implementation of precision medicine are posed differently in Chapter 2 (Study 1) and Chapter 3 (Study 2).
Whereas the primary focus of Study 1 is on the environmental factors that lead to success of precision medicine, the secondary focus of Study 1 is on the policy nature of resistance to precision medicine as currently portrayed in the literature. Study 2 reverses that emphasis.
Study 1 develops an historical envelope around the genesis of precision medicine, why it represents a Kuhnian paradigm shift, why paradigm shifts despite their revolutionary nature require time to convert scientists, how the progress of life sciences inevitably led to precision medicine, and what constitutes parameters for successful implementation. Study 1 then continues with challenging the prevailing explanations to the climate of resistance and offers reasons why these explanations must be extended into inquiries about the
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organizational and community of practice dynamics of resistance – phenomena currently
overlooked in the literature.
By contrast, the thrust of Study 2’s thesis centers on the factors that lead to resistance in communities of practice, in general organizational environments, and in health care settings. This serves as the backdrop to the analysis of three leading institutions which through their success contrast with the climate of resistance and demonstrate that resistance can be overcome with planning and execution of reproducible specific measures. These measures form the underpinnings of the Findings and the Propositions of Study 2 which, therefore, provide an explicit pathway for overcoming resistance and duplicating the success of the three institutions.
Study 2’s principal conclusions, therefore, are twofold:
1. Impact on organizational theories of change: a) the formulation processes of standards of practice are not predicted by prevailing organizational theory; b) the effects of historic paradigm shifts are not anticipated in conventional theories of resistance to change; and, c) the adoption of precision medicine in the face of resistance has implications for theories of change.
2. Implementation of precision medicine: a) the antecedent conditions for precision medicine implementation can be defined in terms of specific organizational and cultural actions that are reproducible operationally across the spectrum of health care providers; b) the positive clinical outcomes of precision medicine can be measured in terms of patient survival and reduced morbidity; and, c) the needs of various stakeholders in precision medicine can be reconciled by aligning standards derived by physician communities of practice with patient expectations and organizational needs.
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CHAPTER 1
INTRODUCTION TO THE DISSERTATION
Precision Medicine in the Biopharmaceutical Industry: A Paradigm Shift
The biopharmaceutical industry and the provision of health care services are amidst a paradigm shift – a fundamental change in the basic concepts and experimental practices and processing of knowledge of a scientific discipline (Kuhn, 1962). A
“paradigm” in the Kuhnian construct refers to all theories, concepts, methods and the like that a scientific discipline, and by extension a professional body, such as physicians, accepts as the basis of discovery, learning and knowing, and the foundation for future
research in that discipline. Paradigm shifts are the basis of scientific revolutions as compared to the incremental advancements in “normal science,” defined by Kuhn as scientific work done within a prevailing framework. A paradigm shift in a scientific field arises when the prevailing paradigm that governs normal science becomes incompatible with new observations (a crisis phase), thus provoking the formulation of a new theory or paradigm, i.e., the scientific revolution.
The rise of molecular medicine originating in the mid-20th century with the
discovery of the structure of DNA in 1953 and culminating in the completion of the
Human Genome Project (terms in Bold Italics are defined in Appendix G) at the turn of
the millennium have inspired a contemporary paradigm shift which is unfolding in real
time. The scientific foundations of the molecular medicine paradigm shift, in other
words, have been evolving over 70 years of positive advancement of knowledge within
the prevailing life-sciences framework. There is, however, a cross-current of three forces:
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1) realizations about the limits of existing pharmaceutical utility; 2) a movement towards
reinvention of the definition and nature of disease; and, 3) disruption of the provision of
care. Together these comprise a crisis in the Kuhnian sense.
This dissertation is a study of how the rapidly emerging clinical field built on molecular principles, better known as precision medicine or “the treatment and prevention of disease that takes into account individual variability in genes, environment, and lifestyle for each person (NIH, 2015),” represents a real-time paradigm shift in the
Kuhnian sense. The notion that these changes constitute a paradigm shift arises because the implementation of precision medicine has provoked resistance by health care providers – at professional and organizational levels -- despite material progress in the development, approval and availability of precision pharmaceuticals and associated companion diagnostics (Pritchard et al, 2017), and evidence that treatment outcomes are improved at lower costs (Haslem et al, 2018). Analysis of the underlying causes of this resistance pose an opportunity to inform organizational change and resistance theory through study of the implementation processes in effect at the few health care providers that have embraced and deliver precision care to their patient populations, as will be explored in Chapter 3 (Study 2).
Application of the Structure of Scientific Revolutions to the Life Sciences
The reference to biopharmaceuticals captures the convergence of small molecule or synthetic pharmacology that dates to the 19th century (the “Synthetic Period”) with large molecule or biologically based pharmacology. This biological transformation originated with production of vaccines in the mid-20th century (although vaccines
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conceptually originated in the 18th century) and arrived as a dominating force in medicinal development during the 1970s with the advent of biotechnology. This transformation persists through the current time and is referred to herein as the
“Molecular Period” which is further elucidated in Study 1.
The tipping point of this dissertation is establishing whether the Molecular Period as defined above constitutes the basis of paradigm shifts in a way consistent with Kuhn.
The history of a body of science or a discipline within science can be characterized as having four phases according to Kuhn. Within the context of this dissertation’s focus on the adoption of precision medicine, these phases can be defined and illustrated as follows:
• The pre-paradigmatic phase – Kuhn describes this phase as the time leading up
to the formation of an initial paradigm as would occur in the assembly of a new
field or discipline. For purposes of this dissertation, however, this phase refers to
the transformation juncture to a new paradigm as scientists process the impact of
an impending scientific revolution. This is generally a point of no-return to prior
norms, but in current circumstances not a binary choice between the Synthetic
and Molecular Periods. The knowledge and methods of the Synthetic Period are
viable for the purposes of medicinal discovery and intervention in disease, but
the limits have become apparent as will be described in Study 1. The Molecular
Period’s scientific advancements and clinical insights, although a work in
progress, can be interpreted as having had elicited a pre-paradigmatic phase.
• The normal science phase – the period of incremental advancement and
refinement that seeks to reconcile prior observations and operates under
prevailing ways of observing and measuring. The normal science phase of the
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Synthetic Period has been operating in parallel with the normal science of the
Molecular Period for about 70 years. These two periods are not in conflict and, in
fact, cross-pollenate. Scientists and physicians for the last three generations are
schooled and typically function with the tools and within the thought frameworks
of both. The Molecular Period, however, has reached a crescendo where the
scientific principles are ready for application to the daily provision of medical
care. In the laboratory, the Synthetic and Molecular Periods may well co-exist
for several more generations, but a new normal clinical science phase is
positioned for adoption as an applied discipline now and, therefore, challenges
prevailing normal clinical science.
• The crisis phase occurs when new observations – or anomalies – challenge the
underlying orthodoxy of the prevailing paradigm. Is there a prevailing orthodoxy
of life science? A prevailing orthodoxy does exist to the extent that disease is
characterized on a morphological basis and the hit-and-miss nature of
pharmaceutical intervention is tolerable within the current models and standards
of health care. To the extent that the Molecular Period and precision medicine
redefine the nature of disease as well as potentially offer an alternative standard
of care and quality outcome, the prevailing orthodoxy is challenged, and a crisis
does exist. Kuhn identifies circumstances when there is a lack of comparability
of approaches to science using a neutral stand as “incommensurability.” The
differences of the Synthetic Period and the Molecular Period do not rise to this
measure of conflict in that both periods acknowledge the same observations in
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chemistry and biology; the shift relates to their convergence and that, as Study 1
will elaborate, is a source of the ambiguity.
• The scientific revolution per se is the re-formulation of the operating framework
for discovery and the explanation of phenomena. In the case of further
confluence of the Synthetic and Molecular Periods, the new orthodoxy is yet to
be defined. Most likely, molecular thought patterns will fully dominate after
additional future generations of scientists and clinicians occupy life science and
health care. The Synthetic Period will largely yield but the new molecular
paradigm will inherit the tools, methods, observations, and still-valid conclusions
of the Synthetic Period.
Thomas Kuhn’s landmark work The Structure of Scientific Revolutions (1962) was drawn from his vantage point as a physicist and focused on the revolutionary events in the physical sciences and cosmology. Of course, the shift that resulted from the
Copernican empirical model of the solar system replaced – with clerical and traditionalist opposition – the Ptolemaic conception of an earth-centered universe. This is perhaps the archetypal “paradigm shift” in that it changed the basic view of humanity’s role in the universe and dealt one of the first blows to the anthropomorphic shaping of existence, thus freeing the Western scientific imagination from classical mythology, the traditional dogma of ancient Greek and Roman philosophy, and Abrahamic scripture. Other paradigm shifts in physics and cosmology later included the Newtonian revolution,
Relativity and Quantum Theory, all of which seem to embody simultaneous truths on the
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one hand and paradigm conflict on the other. These essentially co-exist but provide
challenges for future work.
Once a paradigm shift is settled through the process described above, further
developments take on the identify of normal science. While semantically this might
trivialize the pursuits of scientists, that is not the intention. Within a paradigmatic period
– which often endures over centuries – there are dramatic, sometimes cataclysmic
breakthroughs which smash the punctuated equilibrium of the pace of science. The
brilliant experiments, new tools, and procedures and, indeed, the new fields of study that
emerge are significant, but rarely in any discipline have the effect of changing a world
view, let alone an underlying cosmology or epistemology.
In this author’s investigation of the implementation of precision medicine, raising
the question of what precision medicine represented in the history of life sciences invited
a look at this phenomena through the Kuhnian lens, although with extreme reluctance
because the sharp lines of distinction of new world views in physical sciences were far more subtle in the life sciences. Even during studies as an undergraduate biology major
steeped in Kuhn’s work in a philosophy of science course, this author was always uneasy
with drawing parallels of the intellectual forces at work in each scientific endeavor,
despite the fusions of biology with chemistry, physics, mathematics and complexity
theory that have multiplied during this author’s lifetime.
Biological science, this author was instructed by his undergraduate professors
during the classical period when biology was considered a descriptive science, was one
more reliant on the affirmation of phenomena through cumulative, validated observations
than on theory. Morphology trumped all until experimental biology characterized the life Page 6 | 477
sciences starting in the mid-20th century. Experimental biology’s modus operandi is the
conduction of experiments for the investigation and understanding of biological
phenomena. At the very least it supplements but essentially replaces morphological
biology as a means of validation and expanding insight into anatomical structures and
physiological properties through such methods as molecular analysis, biochemistry, biophysics, ultra-morphology, and interaction within an environment. Experimental
biology over the last generation has begun to yield to theoretical or systems biology
which is built on mathematical modelling and abstractions of life science phenomena.
Kuhn himself acknowledged that his conceptualization of paradigm shifts spoke
loudest in the theory-dependent world of physical sciences. Normal science also
functioned in a more definable way in the physical sciences. Life scientists, on the other
hand, did not enjoy the intellectual economy of their compatriot physicists and chemists.
Normal science for life scientists is more interdependent, less theoretical, and almost
entirely incremental in its advancements (Carlson, 2018).
While the Renaissance anatomical work of Vesalius jettisoned the classical
foundations provided by the Hippocratic canon and Aristotle’s De Anima, the Galenic
humoral concepts of disease associated with classical thinking persisted until replaced
with the Germ Theory of disease in the late Victorian Period.
The history of life sciences does not support the wholesale abandonment of prior
models or paradigms in the face of new discovery. The corpus of biological knowledge,
by and large, is often perennially validated – the human heart of the Renaissance is the
same as the human heart of the 21st century, at least structurally if not spiritually. To put a
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finer point on it, in much the same way as Newtonian principles of gravitation hold up for
practical purposes to this day, classical biological observations and principles remain
largely viable and reliable. For this reason, when the life sciences produce results that
change the world view, there is far greater likelihood that the prevailing paradigm(s) will endure in parallel with the emerging paradigm. Such appears to be the case with what this dissertation describes as the Molecular/Genetics Paradigm. Its origins emerged nearly a century ago, and it has been characterized with steady incremental advances that validate its claims and expand its utility as a foundation for intervention in disease. Precision medicine by being a culmination or synthesis of the scientific products of the
Molecular/Genetics Paradigm, is the clinical or practical threshold for that Paradigm. It is
natural to expect, therefore, that implementation would be resisted in the face of
competing, parallel paradigms that have been true to their missions of intervention in
disease. A corollary question, which this dissertation addresses, is whether the limitations
of the other prevailing life science paradigms constitute a “crisis” of sufficient weight to
tilt precision medicine in the direction of becoming a standard of care that transforms the
therapeutic world view and conception of disease by clinicians.
Table 1 offers a studied but somewhat arbitrary itemization of life science and medical paradigm shifts as posited by this author. The literature either rejects that there are life science paradigm shifts (Tang, 1984), or else grudgingly allows that shifts occur when the roar of intellectual or experimental evidence is too loud to ignore (Carlson,
2018), as is the case in the rise of the Germ Theory of Disease 150 years ago. The list
acknowledges a few of the major normal scientific increments that reinforce the
paradigms but do not themselves rise to the crescendo of a paradigm shift. The paradigm
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Table 1: Author’s conception and delineation of Kuhnian level paradigm shifts in the life sciences and medicine. Characterization and Time period Life Associated normal science significance of science or and notable scientific paradigm shifts medical increments shift Pre-paradigmatic -Pre-Greek Pre- -Book of Genesis phase: ancient medical Golden Age scientific -Homer’s Iliad paradigm precursors -Resurgence in divine -The Perfectionists (19th and the more modern the modern age theories of century) disease as the wages counter beliefs disease of sin -Demonic view of disease, ancient, medieval, and contemporary, e.g., early religious response to AIDS -Emergence of Traditional Chinese Medicine, Ayurvedic Medicine Graeco-Roman 5th century Life Hippocratic (b. 460 BCE) Aristotle’s (b. 384 BCE to the Science corpus of 60 books: disease is BCE) De Anima Renaissance purely naturalistic explainable Anatomical Paradigm only by secular causes and – the first paradigmatic treated only by rational means. basis for rejecting the divine theory of Galen’s (b. 129 CE) disease, describing organization of medical life, and forming the practice basic framework for biological thinking in the West.
Graeco-Roman 5th century Medical Chance response to Hippocratic and B.C.E. to intervention that reinforced the Galenic Pathology Pasteur prevailing belief system Paradigm; conceptualization of Humoralism – chemical the nature of disease systems affecting human and the foundation for behavior – characterized by medical reasoning Alcmaeon of Croton (C. 540– through the 500 B.C.E.) and applied by Renaissance until the Hippocrates to medicine as the rise of the Germ vital bodily fluids, of blood, Theory of Disease yellow bile, phlegm and "black bile"
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Table 1: Continued Characterization and Time period Life Associated normal science significance of science or and notable scientific paradigm shifts medical increments shift Avicenna (b. 980 CE) Turn of the Medical Through mid-19th century: Pharmacology First Rise of natural product Paradigm. Islamic Millennium pharmacology focused on medicine recognition and onwards to disease that the physical the present process of disease time Accumulation of folk wisdom enabled therapeutic correlating cause and effect intervention with natural and synthetic 19th century chemical compounds synthesis knowledge and rise of organic chemistry: The Synthetic Phase or Period:
-Fusion of germ theory with insight into chemical activity
-Rational Design Phase or Period: elucidation of cellular and metabolic disease targets
-Modern principles of rational design
-Modern principles of combinatorial chemistry
-High-throughput screening of pharmaceutical candidates
Vesalius’ (b. 1514) Renaissance to Both -Rise of naturalism Anatomical Structural Victorian -Cataloging of species and Paradigm. Description Period based on anatomical and of structure based on developmental observations empirical observation -Anatomical foundations of allowed observation of medicine anatomical change in -Comparative anatomical the face of disease suggestions of evolution -Origins of scientific surgery
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Table 1: Continued Characterization and Time period Life Associated normal science significance of science or and notable scientific paradigm shifts medical increments shift Darwinian Paradigm. Victorian Life -Further cataloging of Description of Period (Origin sciences Species; refinement of the speciation by virtue of of Species, Linnaeus (b. 1707 CE) natural selection as 1859) and taxonomy of species opposed to onwards to the -Bacteriologic basis of disease traditionalist present time postulated by Koch and conception of static Loeffler (1890) species forms -Demonstration of natural selection with viruses and bacteria
Germ Theory Late Victorian Medical -Effect of sterile technique Paradigm. Recognition Period -Experimental design and of microbes in onwards to the implementation pathophysiology – new present time -Scientific method applied to conceptualization of biology causal nature of -Public health measures disease (John Snow, -Rise of scientific medicine 1813 – 1858; Louis and the Flexner Report (1910) Pasteur, 1822 – 1895) on medical curricula -Rise of vaccination and virology -Emergence of antibiotics -Investigation of micro- pathology across many disease states
Mendelian Genetics Late Victorian Life -Statistical sciences Paradigm. Empirical Period science advancement demonstration of the onwards to the -Reproducible results and principles of heredity present time predictability and the dynamics of -Agricultural advancements generations within through hybridization species. Gregor -Animal husbandry precision Mendel (1822 – 1884) -Fundamentals of disease resistance over time -Reinforcement of natural selection
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Table 1: Continued Characterization and Time period Life Associated normal science significance of science or and notable scientific paradigm shifts medical increments shift Molecular/Genetics Origins at Life -Immunohistochemistry/ Paradigm. Chemical Rockefeller science disease diagnostics and molecular basis of University by -Rise of biotechnology life and heredity Avery in the -Transcription enzymes 1930s; lead to -Genetic recombination publication of -Monoclonal antibodies the structure of -Polymerase chain reaction DNA by -Human genome sequencing Watson, Crick, -Bio-banking/genetic basis of Franklin, and disease correlation Wilkins -Observation of selective (1953); to response to pharmaceuticals present Precision Medicine Conceptualized Medical Reconceptualization of disease Paradigm in 1980s; actualized with Reconstruction of the completion of taxonomy of disease the Human Genome Development of companion Project, 2003; diagnostics evolving in current times Development of genomically to integrated driven precision medicines medical practice Functional intervention in rare diseases Sources: Abu-Asab et al (2013); Afshar et al (2019); Barnes (1984); Cambiaghi (2017); Casadevall et al (2016); Debunardi et al (2010); Flexner (1910); Hoßfeld (2017); Johnson (2006); Nickles (2017); Polansky (2007); Strohman (1997); Vegter (2018); Zargaran et al (2012); Hippocrates (On the Sacred Disease, On Human Nature, Epidemics, c 460 – 420 BCE); Aristotle (De Anima, c. 350 BCE), Aelius Galen (Method of Medicine c 175 CE), Avicenna (Al-Qanun-fi-al-Tibb, c 1010), Andreas Vesalius (De Humani Corporis Fabrica, 1543), Karl Linnaeus (Systema Naturae, 1735), Antoine Lavoisier (Works on Physiology, 1777), Charles Darwin (On the Origin of Species, 1859), Gregor Mendel (“Versuche über Pflanzen-Hybriden,” 1866), John Snow (Mode of Communication of Cholera, 1855), Louis Pasteur (On the extension of the germ theory to the etiology of certain common diseases, 1880), James Watson (The Double Helix, 1968), and classical historical compilations such as The Cambridge History of Medicine (Porter, 2006), The Social Transformation of American Medicine (Starr, 2017), The Eighth Day of Creation (Judson, 1979) and The Structure of Scientific Revolutions (Kuhn, 1962). See also Methodology Section, Study 1 for additional primary source references.
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shifts of the life sciences and medicine are co-mingled here but are distinct in the sense
that life science shifts enable the medical shifts.
Criteria for Determination of a Paradigm Shift
Abstracting from Kuhn, it is possible to formulate four practical criteria for determination of a paradigm shift. From the viewpoint of scientific revolutions or organizational response to a shift, these must be aligned so that they can be applied to organizational readiness and acceptance of a paradigm shift:
• Frames of reference or mind-mapping, i.e., insight into the new discovery and
acceptance of the new truths associated with the new way of thinking;
• Investigational activities, i.e., ways that research approaches have changed in
observable ways;
• Contribution to the new body of knowledge and approaches to validation;
• Approaches to theory formulation and strengthening consistent with the new
paradigm, and whether those questions asked, the procedures followed, data
gathered, and means of analysis are appropriate to the model and metaphors of the
new paradigm.
These practical touchstones will be evaluated in connection with observations
made at three institutions that are acknowledged leaders in the integration of precision
medicine with patient care. These institutions will be interviewed for Study 2, but for
now note that the common element mediating a paradigm shift in medicine in Table 1
concerns the conceptualization and re-conceptualization of the nature of disease. The
National Research Council (2011) and Berman (2018) make particularly strong cases as
Page 13 | 477 to precision medicine’s role in this regard. Paradigm shifts in medicine, therefore, are a second order effect of the Molecular/Genetics paradigm shift in the life sciences which is based on new thought frameworks that are the fundamental basis for the existence of medicine, i.e., the pathologic basis of disease. Pathological studies are the bedrock of medical training and practice and create a momentum that is challenging to divert. This will be the basis of answering the question “Is precision medicine a paradigm shift?” in
Study 1 and will be a keystone in the exploration of why there is resistance to the implementation of precision medicine.
The Convergence of the Pharmaceutical and Biotechnology Industries: Role in the Paradigm Shift
The converged traditional pharmaceutical industry with biotechnology – biopharmaceuticals – is a lynchpin in human health and is now among the largest industries globally. Referring to Table 1, these industries are respectively byproducts of two different paradigm shifts: the ancient Avicenna Pharmacology shift and the contemporary Molecular/Genetics Shift. Industry apparently accommodates to shifting paradigms far more seamlessly than clinical practice. These paradigms were reconciled within a generation of pharmaceutical commerce.
While the United States and several European countries have dominated the innovative dimensions of the industry, the proliferation of biopharmaceutical innovation and production has become universal (Frew, 2007, 2008; Rezaie, 2008; Chakma, 2014), suggesting that as more cultures participate in discovery and development there will likely be a greater breadth of experimentation with fundamental ideas.
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The underlying molecular biology and genetic science on which the
biopharmaceutical industry is built is incessantly dynamic and has challenged the
industry with rethinking its relationship with clinical practitioners throughout its history.
The morphological definition of disease and related interventions were built on life-
science research from the time of John Snow and Louis Pasteur in the 19th century (the
Germ Theory of Disease paradigm shift) and are undergoing reformulation. The
redefinition of disease and related interventions based on molecular insights originating
in the mid-20th century and amplified by the sequencing of the human genome begun at
the turn of the millennium (the Molecular/Genetics and Precision Medicine paradigm
shifts) are the foundations of the seismic shift. The transformation to which this study
refers, therefore, spans the two true modern paradigm shifts in the life-sciences, the explication of which constitutes one of the arguments in Study 1.
The Synthetic Period provided clinicians with diagnostic tools that allowed accurate determination of disease states in infection and inflammation, the cancers, the underlying causes of heart disease such as hypertension and cholesterolemia, and metabolic diseases such as diabetes. The Synthetic Period, more importantly, provided broadcast interventions across the spectrum of disease using pharmaceuticals that had random effects of curing or alleviating disease based on the alignment of a medicine with how disease presented in a population. By focusing on aberrant cellular or metabolic- process targets implicated in disease, pharmacy produced an inventory that addressed hundreds of diseases. Through the late 20th century, the entire global armamentarium of
pharmaceuticals was directed at approximately 483 cellular and metabolic disease targets
(Drews, 2000), i.e., the cumulative product of a century’s worth of drug discovery was
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based on a relatively small library of disease targets. The tools of molecular medicine
now produce hundreds of new candidate targets per year (Sammut, 2012). In those cases
where a physician had an armamentarium of several medicines that could be directed at a
disorder, trial and error often might have provided a successful outcome over time. The
Synthetic Period has produced approximately 2500 pharmaceutical classes approved by
regulatory authorities during its century-long history, most of those over the last 70 years,
or approximately 30 approved new medicines per year on average with a wide annual
variance (FDA, 2019).
The Molecular Period similarly provides clinicians with diagnostic tools, but
these target towards molecular characteristics of a disease as they present in patients
individually. The Molecular Period has provided approximately 1200 medicines since the
first approvals in 1980, an average annual yield similar to the productivity of the
Synthetic Period during that time period. Generally, the Molecular Period has allowed
interventions into previously untreatable and rare diseases or has replaced synthetic
pharmaceuticals in selected clinical indications (FDA, 2019).
Over the last decade, the biopharmaceutical industry has begun to provide
precision pharmaceuticals that target the unique characteristics of a patient and their
disease. This study describes in Appendix B over 150 approved precision medicines
approved since 2010, or approximately 15 per year, representing one-third or more of all approved new pharmaceuticals during that period (Personalized Medicine Coalition,
2018). The number of precision medicines and associated companion diagnostics in the pipeline of the US Food and Drug Administration (2019) approval process exceeds 200
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(appendices 3 and 4), suggesting that over the next 10 to 15 years, about half of
pharmaceutical productivity will be precision medicines.
The Arguments of this Study
Thus, although a subset of each of the outputs of synthetic and biological pharmaceuticals, it can rightly be argued that the industry and medical practice have entered the “Precision Period” – the first argument. Presumably, the Precision Period has
been or will be embraced by the medical community over an unpredictable but not
immediate time frame. As will be shown, there is resistance among clinicians to the
adoption of precision medicine.
The second argument and area of investigation of this study is that at its highest
level, resistance to precision medicine is essentially resistance to the paradigm shift to
molecular medicine that had its roots in the mid-20th century but only now is manifest in
the form of clinical practice options. The medical community has not yet converged on
precision medicine as constituting a standard of clinical care and consequently, apart
from clinical practice guidelines in place at a handful of provider institutions, there are
not yet widely adopted clinical practice guidelines (Lin, 2017; Chow, 2018).
The first and second arguments are the substance of Study 1. The third area of
investigation and related arguments focus on clinical resistance and the ways that such
resistance has been managed at three of the leading American precision medicine
providers. Management of the resistance to precision medicine is the substance of Study
2 which, in addition to positing management principles for the adoption of precision
medicine based on practices at three exemplary institutions, will explore implications for
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theories surrounding resistance to change in organizations and professional communities
during circumstances of a scientific or clinical paradigm shift.
In summary, the five main arguments of this dissertation are:
• One, that precision medicine represents a paradigm shift in health care (Study 1).
• Two, that resistance to precision medicine is essentially resistance to the paradigm
shift to molecular medicine that had its roots in the mid-20th century (Study 1).
• Three, clinical resistance to precision medicine exists and that there are
determinable and manageable reasons for this resistance (Studies 1 and 2).
• Four, that the managerial strategies in place at leading institutions are definable
and reproduceable in other clinical environments (Study 2).
• Five, observations concerning resistance to precision medicine and their
management have implications for theories of organizational change (Study 2).
Definitions and Settings
The medical community has converged on this definition of precision medicine as articulated by the US National Institutes for Health (2015): “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” Precision medicine as a term replaced
“personalized medicine” following a publication of the National Research Council (2011)
that argued that precision is a better term because it classifies population subgroups based
on genomics. In summary, precision medicine is a fundamental change in the way
medicine can be practiced and delivered by strengthening in parallel prevention,
diagnostic and therapeutic strategies through treatments designed for each patient. While
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these have been goals of medicine since the times of Hippocrates (c. 460 – c. 370 BCE)
and the Greek mythological god Asclepius, the convergence of technological capability
built on the scaffold of genomics represents a paradigm shift of no less consequence as the emergence of the Germ Theory of medicine in the 19th century.
With respect to the operational setting of precision medicine, health care is
provided through a network of providers, producers and payers which work together
despite varying business models. The impact of different business models among
stakeholders in precision medicine is at a higher level of complexity and need for
reconciliation than exists in the current care environment. Table 2 identifies the stakeholders in precision medicine; it does not differ substantially from health care
Table 2: Principal stakeholders in precision medicine
Patient Related Government/ Provider Related Producer Related Payer Related other Patients and National Physicians Pharmaceutical and National insurance families authority biotechnology programs companies Patient advocacy Accreditation Provider Diagnostics Private health groups agencies organizations manufacturers insurers Coordinators/ R&D hubs Specialty Diagnostic Government concierge services communities of laboratories employee funds practice and guilds Genetic R&D institutes Biobanks and Device and Patient out-of- counsellors information equipment pocket payments repositories manufacturers Academic health Private life centers insurers National hospital systems Not for profit and for profit community hospitals NGOs Source: Ginsberg, 2018 and this author’s conception
generally, but has a few additional participants. While a study of incorporation of precision medicine into medical standards of practice may appear a natural process, it is still Page 19 | 477
emerging. The organizational and professional dynamics of the field, therefore, may have
implications for management theory on the resistance to change.
Is resistance to precision medicine unique in medical history? Historically, patterns
of medical practice embrace the opportunity for clinical improvements much less rapidly
than intuition would suggest. Our intuitive expectations of seamless integration with
standards of care derive from a few celebrated examples of when there was a publicly
visible, rapid pace of adoption. These examples illustrate the point:
Although an ancient disease, the first polio epidemic recorded in the United States
was in 1894 and panic grew over the next sixty years as polio struck in waves hundreds of
thousands of people and triggered the creation of the National Foundation for Infantile
Paralysis (“March of Dimes” campaign) in 1938 by President Franklin Delano Roosevelt
which further fueled awareness and terror surrounding the disease. When the injectable Salk
vaccine (formulated with killed virus) was approved in April of 1955 there was an immediate cascade of national inoculation activity. Seven years later when the Sabin oral polio vaccine (formulated with attenuated virus) was approved there was a similar public
response despite the massive reduction in cases of polio following the Salk vaccine. The
social formula was the combination of awareness and fear which ultimately was met with an
inexpensive intervention – dedicated to the public through no filings of patent claims – that
was relatively simple to administer (Trevelyan, 2005).
An example of a stunning adoption of a therapeutic agent surrounds the US
regulatory approval in January 1984 of cyclosporin-A, an immunosuppressive agent which
rapidly became essential to organ transplantation. Prior to the availability of cyclosporin-A,
rejection of transplanted organs, such as kidneys, hearts, and livers, was managed with a
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combination of steroids and an immunosuppressive called azathioprine introduced in 1957.
The results of transplants managed with this combination, actuarially measured in “graft survival,” was a disappointing one year. Consequently, the decision to provide an organ transplant for a patient was made on a conservative basis.
The promising use of cyclosporin-A during US clinical trials in the late 1970s and early 1980s, and approved use in Europe during 1983, was observed closely by US transplant physicians who during 1983 became more conservative in selecting patients for kidney transplantation, anticipating in short order a new standard of practice that would improve patient outcomes. Once the clinical trial data was unblinded and graft survival rates seen to more than double, transplants were delayed until the anticipated approval and release of cyclosporin-A. Once released, substitution was immediate, a standard of practice arose spontaneously among transplant physicians, and the revolution in transplantation assured.
The factors at work here differed from the population-wide experience with polio vaccines: the community of transplant physicians was small and comprised of mostly science-oriented academic physicians – a true community of practice. The clinical trials were conducted by the key opinion leaders in the field. The pharmacokinetics were fully elucidated and the mechanism of action of cyclosporin-A was highly characterized and acceptably precise. The clinical stakes were very high for the patients and, although upon its release cyclosporin-A was the most expensive pharmaceutical up to that time, the cost benefit analysis relative to the entire cost of caring for end-stage organ failure patients and re-transplantation was persuasive enough for the payers to approve coverage (Sammut, 1984).
Another example concerns management of HIV. Although the story of the introduction of the protease inhibitors or anti-retrovirals (ARVs) for HIV intervention
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followed a similar pace of rapid introduction, at least in the developed world, that pace
emanated for different reasons. ARVs slowed or reduced the viral load of HIV, the virus that
causes AIDS, in people already infected. The prognosis for people infected with HIV was
grim. From the recognition of AIDS in June 1981 until the approval of the first ARV in
1995, people living with HIV/AIDS garnered significant political influence and through
activism promoted the development and availability of these essential pharmaceuticals over
a time-frame that was historically rapid, although not rapid enough for infected people in the
developed and especially the developing worlds. HIV/AIDS has also had the effect of
framing disease and social response as a human rights matter, a position eloquently
articulated by the late Jonathan Mann (Fee, 2008). Demand for intervention and political
empowerment propelled rapid adoption and financial reimbursement. Furthermore, the
community of practice, i.e., physicians caring for HIV/AIDS patients was relatively small
and generous in the exchange of information, thus promoting the rapid formulation of a
standard of practice in HIV/AIDS care (Vella, 2012).
In the matter of medical procedures, the proliferation of the less-invasive procedures of percutaneous (“key-hole”) surgery and interventional radiology (e.g., dilation of cardiac arteries) within a decade of introduction in the mid-1980s stand as examples of rapid adoption, again for different reasons. Rapid uptake of these device-driven procedures was propelled by a myriad of factors: patient safety and recovery; cost-containment through reduction in hospitalization; technology enablement through better imaging systems and advanced biomaterials; incentivization for the administering physician; and, acceptable economic incentives for producers to promote innovation. These elements all combined to re-establish standards of practice for alternatives to invasive procedures. The adoption of the
Page 22 | 477 pharmaceutical and medical technologies above, however, are exceptions rather than the rule for adoption rates of new interventions in health care more generally (Schlich, 2016).
By way of contrast, the game-changing innovations described above were important, but all were representative of the progress, tenets, and normal science of the Synthetic
Period. Despite their significance, they were not a function of a paradigm shift in the underlying science or standards of clinical practice.
Essential Definitions of Pharmaceutical Commerce and Therapeutics
For purposes of this dissertation, the biopharmaceutical industry refers to those innovative medicines companies that discover, develop, manufacture and distribute through elaborate detailing to physicians and hospitals, those medicines and vaccines
(“therapeutics”) that are under patent protection and trademarked, i.e., the proprietary products of innovation. This study excludes those companies that manufacture and distribute those therapeutics that are off-patent and sold as generic equivalents of formerly proprietary products. The essence of the distinction is “innovative” companies versus generic companies. The former companies are subject to the dynamics of a paradigm shift whereas the latter companies are immune.
In this study, “therapeutics” refers to a variety of interventions based on active pharmaceutical ingredients or “APIs” intended to produce a desired metabolic or immune change in the patient or elicit a preventive response upon an infectious challenge to the body. APIs fall into the two basic categories of pharmaceuticals described earlier: chemical or small molecules which are developed and manufactured through chemical synthesis, and biologic or large molecule (biological) medicines that are discovered, developed and manufactured from living materials which typically include human cells
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or tissues, animals, plants and microorganisms. Biologicals are called large molecules
because they are comprised of proteins or peptides that are larger and heavier than those
molecules and compounds in organic chemical structures. Biologicals generally must be
transfused into a patient and usually not administered as pills. Biological pharmaceuticals
include medicines built around recombinant-DNA, monoclonal antibodies (MAb), gene and cell therapies and stem cells. Both small molecules and biologicals are represented
among precision medicines.
Motivation and Impact of Research
The motivation for this research is inspired and informed by the curious case before
us now: the adoption of precision medicine. Precision medicine, as we will see, is a
paradigm in and of itself, or at least the clinical-operational phase of a paradigm shift which
arbitrarily originated in 1953 with the publications of the structure of DNA (Watson &
Crick, 1953; Franklin & Gosling, 1953; Wilkins et al, 1953). Investigation of DNA was rooted in work by Oswald Avery at the Rockefeller University begun in the 1930s (Avery et al, 1944). Precision medicine conceptually was postulated in the 1980s and gradually won- over scientific and public funding support. As an idea, it was enabled at the turn of the millennium with the completion of the Human Genome Project (US Department of Energy,
2019) but has been marred by a slow pace of acceptance as a viable approach to patient care.
A study of the reasons for this slow penetration is warranted from a patient care point of view but is also suggestive of other elements at work in clinical decision making at organizational levels (PMC, 2017), development of professional standards of practice and individual physician behavior.
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It is the gap in the study of antecedent conditions in the implementation of precision medicine in which this research originates. The organizational and practitioner behavior aspects of this investigation are seated in the concept of the paradigm shift, a concept discussed at the start of this Introduction. To review, fundamentally Kuhn contrasts paradigm shifts, which characterize a scientific revolution, such as the post-
Copernican description of the cosmos, to the activity of “normal science” or scientific work done within a prevailing framework or paradigm, that is to say what the members of a given scientific community have in common in the way of underlying beliefs, values and methods of study or epistemological certainty. When new observations are not resolvable with prevailing knowledge, the adoption of a new theory or paradigm emerges.
In hindsight, the emergence of a paradigm shift might appear logical and seamless, but it may take decades or even a century for a scientific community or a community of practice to embrace the new principles and practices, techniques and epistemological implications for ways of knowing, observing and processing knowledge as described above. Sometimes the passage of time is insufficient for total acceptance, especially when the shift challenges prior beliefs or paradigms that are not built on reason or observation, e.g., classical (Aristotelian) or theological (Judeo-Christian revelation) understanding vis-à-vis the Copernican and Darwinian paradigm shifts.
In the case before us, part of the problem of resistance may be embedded in the broad and tentative definition of precision medicine offered by the NIH. As stated above, there is an implication that precision medicine will not fully characterize the practice of medicine and the development and use of biopharmaceuticals for many decades. There are, however, implications that require immediate planning by the three participants in the health
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care milieu: providers (physicians, health professionals, hospitals, clinical laboratories, other
facilities), producers (pharmaceutical, biotechnology, medical device and other developers
and manufacturers), and payers (the managers – governments, insurers – of pooled risk
reserves for the reimbursement of health care costs whether the markets involved reside in
the developed world or the developing world).
This study explores the perception and reality of the pace of adoption of the
precision medicine paradigm and delves into the processes that promote or inhibit that rate
of adoption, with focus on the internal organizational dynamics of health care provider
organizations, the provider-producer interplay, and some reference to payer interplay.
Among proponents of precision medicine, there is a consensus that the pace of adoption has
been delayed. An array of reasons is offered to explain this apparent slow pace.
Pritchard et al (2017) – the seminal paper on resistance to precision medicine –
assembles key challenges to clinical adoption in five categories: 1) lack of education and
awareness, 2) limited patient empowerment, 3) value skepticism by the medical community,
4) required infrastructure and information management capacity, and, 5) impact on care delivery practices. Beyond Pritchard et al (2017), a sixth category concerns outdated public policies in regulation and financial reimbursement. The focus of this study offers another
category that supersedes the above, namely how the organizational dynamics of the most
advanced existing precision medicine programs overcomes organizational and professional
resistance and inertia. Such an analysis is not yet specifically addressed in business or health
care research.
There are other obstacles to precision medicine. Among critics of precision medicine there is a view that the proponents of precision medicine have grossly exaggerated the
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potential of an approach that is not meeting expectations. Genetically guided therapies, they contend, have not and will not improve population health and, therefore, medicine should move towards health care tailored for the average person (Szabo, 2018). Critics elaborate that genetically based interventions address the needs of only small subsets of patients with specific and rare genetic mutations. Given the increased cost of diagnosis and intervention, cost-benefit analysis – they contend – does not support precision medicine. This debate has been waged for about 15 years with little change in the arguments and no resolution.
Another interpretation of the role of precision medicine has been offered by Berman
(2018). He postulates that precision medicine is not devoted to finding unique treatments for individuals based on analyzing their individual DNA. To the contrary, he contends, the goal of precision medicine is to find general treatments that are highly effective for large numbers of individuals who fall into precisely diagnosed groups. Disease develops over time, he writes, through a sequence of defined biological steps, which may differ among individuals based on genetic and environmental conditions. Precision medicine is positioned to develop rational therapies and preventive measures based on a precise understanding of the steps leading to the clinical expression of diseases. This conceptualization might resolve some elements of the conflict. Be that as it may, Berman (2018) will be revisited later in
Study 1 when answering the question of precision medicine as a paradigm shift.
This dissertation describes the challenges as articulated by the proponents and the arguments offered by the critics in a systematic, objective way but adds the missing components of organizational dynamics. Both sides in the debate agree that the adoption of precision medicine is behind schedule, but for different reasons. A critical question in
Page 27 | 477 addressing this debate is whether the root causes are a function of a lack of precision pharmaceuticals and companion diagnostics.
To answer the question of precision medicine capability and capacity, Study 1 of this dissertation provides a quantitative analysis and assessment of precision medicine pharmaceuticals and companion diagnostic tests either on the market or in the developmental pipeline. The analysis explores the range of clinical indications of these products and provides data quantifying global demand for precision medicine. Elucidation of the data and circumstances might answer the question of readiness and suitability of precision medicine to serve populations and thus serve to inform the issues in the debate, one way or the other. But this is not the core objective of this study.
It is the desultory and punctuated progress towards the incorporation of this new paradigm that invites a question that when a paradigm shift emerges is there a basis for and explanation of resistance to change in organizational or professional practice communities, i.e., communities of practice? An organizational – behavioral inquiry into the adoption of precision medicine may inform the literature on resistance to change.
The motivation and anticipated impact of this research, therefore, is rooted in personal engagement in the biopharmaceutical industry over nearly a half-century, during which time the author’s professional focus was on the products of the Molecular Period.
Although filled with progress towards intervention in disease and alleviation of suffering, this period was not delivering care through a clinical or commercial model that was commensurate with the underlying scientific advances. Precision medicine, however, potentially exploits the progress of 70 years of scientific achievement and offers a rescue to a prevailing practice of medicine that falls short of meeting patients’ needs. The
Page 28 | 477 realization of precision medicine’s potential, however, is attenuated by resistance to the paradigm shift that it represents. The research presented herein seeks to unpack organizational and professional practice resistance to change and in doing so unlock the realizable potential for human health. Furthermore, the lessons likely embedded in the precision medicine resistance story have broader implications for organizational theory.
[END OF INTRODUCTION]
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A MAP THROUGH CHAPTERS 2 (STUDY 1) AND 3 (STUDY 2):
OUTLINE, CONTENT, AND THRUST
Summary of Study 1: The Pathway to Precision Medicine
Research Questions
Study 1 presents several research questions that will be explored and answered in
turn:
Question 1: Is the practice of medicine undergoing a paradigm shift towards
precision medicine?
Question 2: What is the status of precision medicine therapeutic offerings?
Question 3: What is the status of precision medicine diagnostic offerings?
Question 4: What are the economic and commercial realities of precision
medicine?
Question 5: If conditions indicate that precision medicine is a paradigm shift,
what are the implications for organizational and professional practice?
Evolution of Research and the Emerged Structure of Studies 1 and 2
A narrative on the process that led to this dissertation is itself revealing about the question of whether precision medicine is a paradigm shift. The focus of this research began as an inquiry into the causes for the slow pace of adoption of precision medicine by health care providers even though the field is rooted in the foundational biological paradigm – the Molecular Period – that emerged with the publication of the structure of
DNA (Watson & Crick, 1953; Franklin & Gosling, 1953; Wilkins, et al 1953). The original intention of this research sought to test hypotheses drawn from consensus in the
Page 30 | 477
literature regarding the pace of precision medicine adoption and remedies for the
apparent resistance by the health care community. In preparation for this research, informal preliminary discussions, interviews, and public forums attended over a one-year
period revealed a surfeit of professional opinion largely unsupported by accumulated and
analyzed evidence. Most importantly, the publications, discussion groups and
conferences focused on the rate of precision medicine adoption recounted clinical and
policy issues, not the organizational dynamics of the provider organizations, the
misalignment of business models, or the lack of a coherent approach to the development
of standards of practice for precision medicine – missing pieces that this dissertation addresses.
Study of a relatively new field is hazardous regarding separating opinion from documented evidence, especially when the most-invested community of practitioners finds itself in the minority of opinion as to the relative benefits of the emerging approaches, as is the case in precision medicine. Positions quickly become political or ideological to no truly productive end.
Gradually, a realization emerged for this author that inquiry into the pace of adoption of precision medicine leads to a more general problem concerning why there is organizational or professional resistance to a historical change in ways of thinking. The questions posed in Study 1 lay the groundwork for the superordinate themes of Study 2,
namely “Where precision medicine has been adopted or is under evaluation, what are the
positive components, where is the resistance in arriving at delivery programs and
subsequent standards of practice, and how are these managed?” The semantic trap of
applying the term “paradigm shift” ideally is avoided because what started as an
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eloquently and narrowly defined concept by Thomas Kuhn (1962) has devolved into a
meaningless buzzword often applied to insignificant changes in ways of managing
everyday tasks. Nevertheless, this investigation argues that precision medicine is one of
the few genuine paradigm shifts in life sciences and health care. Or, at the least it
represents the implementation arm of the molecular medicine revolution begun in the
1930s by Avery et al (1944), established with landmark publications of the structure of
DNA (Watson & Crick, 1953; Franklin & Gosling, 1953; Wilkins, et al 1953) and
enabled with the completion of the Human Genome Project in 2003. In their entirety,
Studies 1 and 2 posit that the positive implications of precision medicine will not be fully
realizable until the profundity of its meaning in organization terms, i.e., to the medical
professions, health care institutions and product producers, is rigorously vetted and put
into the historical perspectives of medical communities of practice and clinical practice
guidelines.
Abbreviated Methodology of Study 1
To answer the research questions, the research methodology of Study 1 has two components: 1) historiography (in two elements) and, 2) quantitative analysis of product offerings and their clinical applications.
Methodological Component One is a historiography of two key elements. The first element is an analysis of the history of medicine and the life sciences within the framework of the Kuhnian paradigm shift model. The sources for the first element of history are primary readings of classical original texts. The second historiographic element of Study 1 chronicles the development of precision medicine within the larger context of organized medicine, medical practice, and the evolution of the
Page 32 | 477 biopharmaceutical industry. This chronicle is supported by extensive secondary references. The function of these two elements of history is to establish the argument that precision medicine is itself part of a paradigm shift and that the first order challenge to the implementation of precision medicine is a function of resistance to any classical paradigm shift.
Methodological Component Two: The second methodological component of
Study 1 is quantitative. It is comprised of original inventories and statistical groupings of the clinical applications of approved precision medicines and related diagnostics, and an additional inventory and statistical grouping of the same products currently in the global development pipeline (Appendices 2 through 4).
Conclusion of Study 1
Study 1 provides the historical, scientific, clinical, and commercial contexts of precision medicine as described in the literature, and an additional review of the relevant literature related to the formulation of standards of clinical practice. These efforts are directed at establishing the research framework for the second study and provide a basis on which to draw conclusions regarding the arguments on both sides of the implementation debate. Moreover, Study 1 establishes the framework of the three research questions in
Study 2, the answers to which might provide new insight for the organizational literature related to resistance to change.
Study 1 provides a review of the precision medicine literature, related articles on paradigm shifts, theoretical literature on resistance to change, an additional review of the relevant literature related to the formulation of standards of clinical practice and
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resistance to change in the adoption of a new clinical paradigm. Study 1 builds a case that
the biopharmaceutical enablement of health care has contributed to the development of health care overall historically, and that the emergence of precision medicine is an inevitability in the course of pharmaceutical history and especially the Molecular Period.
Study 1 demonstrates that the inventory of precision medicines and related diagnostics is
established and growing across several categories of disease, and that standards of
practice are emerging but stymied by key business model misalignments despite progress
on the regulatory and economic fronts.
The arguments and conclusions are directed at establishing the research
framework for Study 2, which investigates progress in implementation at three of the
established and exemplary providers of precision medicine. Such inquiry is informed by
the conclusion of Study 1 that capability is currently in place, at least in wealthy
societies, and will grow dramatically. It also posits that demand for precision medicine is
universal even if capacities in health systems – in industrialized and emerging markets –
requires further investment and development. Thus, scientific circumstances, clinical insight and available technologies and products create a milieu of readiness for precision medicine. Despite that readiness and the urgency for adoption, the migration of the
Precision Medicine Paradigm is lagging most likely because the organizational
antecedents for implementation have been insufficiently studied and incorporated into
systems planning. The five research questions, therefore, are answered adequately to
justify the inquiries of Study 2.
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Study 1 Outline: The pathway to precision medicine
Introduction Research Questions Theoretical Framing Literature Review Precision Medicine Evolution Dueling business models Impact in pharmaceutical development The producer dimension Historical capsule of medicinal discovery A conceptual model The rise of precision medicine Theoretical and managerial challenges Convergence of forces Scientific, clinical, and demographic factors Commercial forces Social Forces 1980 as the pivot year Foundational Thinking for the Antecedent Conditions and Consequences Factors suggesting a paradigm shift Why and how organizations resist Characterizing the obstacles Revisiting the Arguments Research Questions, Methodology and Data Sources Methodology Data Presentation and Analysis Framing Argument One Use and abuse pf “paradigm shifts” Factors influencing and signaling a paradigm shift The economics of a paradigm shift Institutional theory applied to precision medicine adoption Evidence for Argument One Framing Argument Two Evidence supporting argument two Profile of approved medicines Profile of companion diagnostics Profile of global development pipelines Economic considerations Precision medicine development in a global context QED: Precision Medicine as a Paradigm Shift Invites Resistance A Conclusion of Study 1: Evidence for a Paradigm Shift Is there resistance to the normal science of the Molecular Period? Summary of Conclusions of Study 1
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Summary of Study 2: An Exploration of Provider Organizational and Decision Dynamic Readiness for Precision Medicine in the United States Outline, Content, and Thrust
Research Questions
As established above, the analysis and conclusion of Study 1 establish the following research questions for Study 2:
Research Question One: Foundational concerns – What are the antecedent conditions for precision medicine to be incorporated into strategies for care delivery and guidelines for professional practice?
Research Question Two: Provider readiness – How is precision medicine positioned operationally to be incorporated into patient care based on cultures and systems established at exemplary institutions?
Research Question 3: Change dynamics – What are the implications of the
pace of adoption of the precision medicine paradigm at the exemplary institutions
for the field of organization theory, in particular, its subfield of resistance to
change?
Abbreviated Methodology of Study 2 The approach taken in Study 2 is qualitative, interview-driven investigation, within the Grounded Theory framework. In the preparation for the Study 2 research, the author explored the scientific, clinical and organizational theory literature widely, attended several precision medicine conferences and had discussions or meetings with thought leaders in precision medicine and health care organizational theory, all in search of finding and articulating testable hypotheses. Based on inconclusive and inconsistent inputs from providers engaged in precision medicine, Grounded Theory emerged as the
Page 36 | 477 ideal methodology because conclusions and possible theory are derived inductively based on questions addressed through a collection of qualitative interviews structured to find thought patterns among the interviewees through language analysis and coding (Glaser &
Strauss, 1967; Martin & Turner, 1986; Strauss & Corbin, 1990).
Scholarly Objective of Study 2
The scholarly output of Study 2 is not to make a case to support one side or the other in the debate over the utility or practicality of precision medicine – although that is a potential collateral outcome – but to interpret the arguments as to what they suggest about the processes at work in clinical decision making within: medical communities of practice, at organizational levels, during development of professional standards of practice, individual physician behavior and the formulation of value judgements behind each of these. An objective and significant contribution of this dissertation as embodied in Study 2, therefore, probes whether these observations might contribute to the theoretical literature on organizational change, especially as related to decisions made by medical communities of practice and at individual professional levels within an organizational context related to standards of practice or clinical practice guidelines.
Study 2 builds arguments around collected qualitative data regarding the forces affecting the implementation of precision medicine, and the internal working of health care providers currently incorporating precision medicine. Specifically, Study 2 drives towards conclusions for the following:1) establishment of antecedent conditions for implementation of precision medicine; 2) determination of requirements for acceleration of precision medicine; 3) postulation and interpretation of metrics for determination of impact of
Page 37 | 477 precision medicine; 4) approaches to the reconciliation of the different business models of the stakeholders in precision medicine; 5) implications of the antecedents to precision medicine to organizational theories of change; 6) implications for organizational theory surrounding formulation of clinical standards; 7) implications for organizational theory related to resistance to change, especially to historic paradigm shifts.
Study 2 Outline
Introduction to Study 2: Paradigm Shifts and Resistance to Change in Scientific and Medical Practice Study 2 Objectives: The Significance of this Research Literature Reviews: Theory Addressing Resistance to Change The Precision Medicine Paradigm Shift as “Change” Defining the concept of change: organizations vs communities of practice Do communities of practice function similarly to organizations in matters of change? General organizational theory on resistance to change Health care organizational theory addressing resistance to change Approach to Formation and Exploration of Research Questions Basis for Selection of the Institutions Alpha, Beta and Gamma Research Questions, Methodology and Data Sources for Study 2 Analytic Framework for Interview Data Interview Themes and Questions Conducting the Interviews Driving Towards Interpretation and Conclusions Interviews: Summary of Findings and Derivation of Propositions Discussion and Conclusions from Interview Findings Grounded Theory Families and the Cascade of Issues Propositions and their Implications Congruity of findings with organizational literature on change Incongruity of findings with organizational literature on change Do the peculiarities of implementing precision medicine inform the organizational literature? Synthesis of Studies 1 and 2: Lessons from the Research
Limitations of the Study Opportunities for Additional Research
[END OF MAP THROUGH STUDIES 1 AND 2]
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CHAPTER 2 (STUDY 1)
THE PATH TO PRECISION MEDICINE
Introduction
The general introduction mapped out the path and plan for this research. The overall inquiry is aimed at determining the causes of resistance to the adoption of precision medicine by the health care provider community at large that expand the explanations that have been published by Pritchard et al (2017) and others. Study 1 demonstrates that precision medicine represents a paradigm shift in the sense of Thomas
Kuhn’s framing of the concept, including a description of the crisis factors that are driving the paradigm shift. In addition, Study 1 describes the history of precision medicine within the context of the biopharmaceutical industry and how it is currently positioned within health care. In order to make a compelling case for precision medicine,
Study 1 also describes the status of currently available medicines and diagnostics that fit into the category as well as those under development. The economics and demand of precision medicine on a global basis are also addressed.
In short, the building of five arguments are promised in Studies 1 and 2:
• One, that precision medicine represents a paradigm shift in health care (Study 1).
• Two, that resistance to precision medicine is essentially resistance to the paradigm
shift to molecular medicine that had its roots in the mid-20th century (Study 1)
• Three, clinical resistance to precision medicine exists and that there are
determinable and manageable reasons for this resistance (Studies 1 and 2).
• Four, that the managerial strategies in place at leading institutions are
reproduceable in other clinical environments (Study 2).
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• Five, observations concerning resistance to precision medicine and its
management have implications for theory of organizational change (Study 2).
Study 1 addresses arguments One and Two and builds the foundation for argument Three. Study 2 will complete argument Three and provide the empirical
evidence through semi-structured interviews for arguments Four and Five. Study 1
provides a discussion of the precision medicine literature and general articles on
paradigm shifts as well as those relevant to precision medicine. Study 2 reviews
theoretical literature on resistance to change with an emphasis on health care and
medicine, the relevant literature related to the formulation of standards of clinical practice
and resistance to change in the adoption of a new clinical paradigm. Study 2 also explores
the literature on organizational behavior of communities of practice.
Study 1 also builds a case that the biopharmaceutical enablement of health care
has contributed to the development of health care overall historically, and that the
emergence of precision medicine, despite being an inevitability in the course of
pharmaceutical history, is a function of the Molecular Period. Study 1 demonstrates that the inventory of precision medicines and related diagnostics is established and growing across several categories of disease, and that standards of practice for implementation of precision medicine are emerging but stymied by key business model misalignments despite progress on the regulatory and economic fronts, a question which is further developed in Study 2.
Again, Study 1’s arguments and conclusions are directed at establishing the research framework for Study 2, which investigates progress in implementation at the
Page 40 | 477 three established and exemplary providers of precision medicine. Such inquiry is informed by one of the conclusions of Study 1 – that precision medicine capability and capacity are currently in place, at least in wealthy societies, and will grow dramatically.
Study 1 demonstrates that demand is universal even if capacities in health systems – in industrial and emerging markets – requires further investment and development. Thus, scientific circumstances, clinical insight and available technologies and products create a milieu of readiness for precision medicine.
Despite that readiness and the urgency for adoption, the migration of the precision medicine paradigm is lagging most likely because the organizational antecedents for implementation have been insufficiently studied and incorporated into systems planning.
The five research questions, therefore, are answered adequately to justify the inquiries of
Study 2. The Research Questions of Study 1 begin the inquiry.
Research Questions
Study 1 presents five research questions formulated to support Arguments One and Two which will be explored and answered in turn:
• Question 1: Is the practice of medicine undergoing a paradigm shift towards
precision medicine and, if so, what are the drivers?
• Question 2: What is the status of precision medicine therapeutic offerings?
• Question 3: What is the status of precision medicine diagnostic offerings?
• Question 4: What are the economic and commercial realities of precision
medicine?
• Question 5: If conditions indicate that precision medicine is a paradigm shift,
what are the implications for organizational and professional practice?
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These questions are interdependent and are approached based on three methods:
historiography (Study 1), empirical review of available precision medicines and
diagnostics (Study 1), and Grounded Theory (Study 2), i.e., construction of theories
through gathering and analysis of interview data. This investigator has chosen to study
the implementation of precision medicine on an inductive basis and has collected data to
show how the phenomenon of precision medicine operates within an evolving Kuhnian
paradigm in the life sciences and as such leads to insights that were not predictable at the
outset. An explanation of how the research took the present course informs the structure
of the present inquiry.
Theoretical Framing
A narrative on the process that led to this dissertation is itself revealing about the
question of whether precision medicine is a paradigm shift in its own right or a
manifestation of the more widely recognized paradigm shift towards molecular medicine.
The focus of this research began as an inquiry into the causes for the slow pace of
adoption of precision medicine by health care providers even though the field is rooted in
the foundational biological paradigm or Molecular Period that emerged circa the publications of the structure of DNA (Watson & Crick, 1953; Franklin & Gosling, 1953;
Wilkins, et al 1953). In preparation for this research, preliminary discussions, interviews,
and public forums held over a two-year period revealed a surfeit of professional opinion largely gathered by surveys, e.g., Pritchard (2017) but not challenged by accumulated and analyzed evidence from institutions fully engaged in precision medicine. Most importantly, the publications, discussion groups and conferences that were focused on the rate of precision medicine adoption recounted clinical and policy issues, not the
Page 42 | 477
organizational dynamics of the provider organizations, the misalignment of business
models, problems of cost and reimbursement, or the lack of a coherent approach to the
development of standards of practice for precision medicine – missing pieces that this
study addresses.
As stated previously, study of a relatively new field is hazardous with respect to
separating opinion from documented evidence, especially when the most-invested
community of practitioners finds itself in the minority of opinion as to the relative
benefits of the emerging approaches, as is the case in precision medicine.
Gradually, a realization emerged for this author that inquiry into the pace of
adoption of precision medicine leads to a more general problem concerning why there is
organizational or professional resistance to a historical change in ways of thinking. The questions posed in this Study 1 lay the groundwork for the superordinate theme of Study
2, namely “Where precision medicine has been adopted or is under evaluation, what are
the positive components, where is the resistance in arriving at delivery programs and subsequent standards of practice, and how are these managed?”
There is a semantic trap of applying the term “paradigm shift” because what
started as a narrowly defined concept by Thomas Kuhn (1962) has devolved into a
meaningless buzzword often applied to insignificant changes in ways of managing
everyday tasks. Or put in Kuhn’s terms, the products of “normal science” are inflated as
the basis for radical new approaches to providing health care. While breakthroughs
characterize virtually every aspect of diagnosis and intervention, these are within the
prevailing theoretical or epistemological frameworks, described in the Introduction as the
Synthetic Period and the Molecular Period.
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This study argues that precision medicine is one of the few genuine paradigm shifts in life sciences and health care. Or, at the least, it represents the implementation
arm or the foundation of the new “normal science” of the molecular medicine revolution
begun with the 1953 publications on the structure of DNA. In its entirety, the research
herein posits that the positive implications of precision medicine will not be fully
realizable until the profundity of its meaning in organization terms, i.e., to the medical
professions, health care institutions and product producers, is rigorously vetted and put
into the historical perspectives of medical practice and clinical practice guidelines.
Practical Framing
There is a litany of benefits, critics say unkept promises, of precision medicine that appear in white papers and numerous reports. One summary is offered by the Personalized*
Medicine Coalition’s 2017 Annual Report. It offers that personalized
medicine benefits patients and the health system by:
• Shifting the emphasis in medicine from reaction to prevention
• Directing targeted therapy and reducing trial-and-error prescribing
• Reducing adverse drug reactions
• Revealing additional targeted uses for medicines and drug candidates
• Increasing patient adherence to treatment
• Reducing high-risk invasive testing procedures
• Helping to control the overall cost of health care (PMC, 2017).
Such an array of potential attributes cannot be ignored and indeed the topic of precision
medicine is ubiquitous in the medical literature. Gameiro (2018) searched the
------*The terms “personalized,” “individualized” and “precision” medicine are used interchangeably.
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PubMed/Medline data base in March 2018 and reported finding 29,884 articles
worldwide, with half being published since 2015. The authors reviewed selected papers
through the “4P lens” described by Hood (2006): prediction, prevention, personalization,
and participation. This lens magnifies the need to transition from traditional reactive
medicine to targeting disease before there are symptoms. The term “reactive medicine”
aptly captures the notion of intervention in disease once clinically apparent. The popular
rejoinder to that principle is the oft described notion of preventive medicine which is
largely limited to focusing on risk factors associated with a disease. This is, of course, an
idealized approach to medicine and is pursued in the framework of public or population
health. References to precision medicine, by contrast, focus on treatment and prevention
for individuals based on unique markers and genetic signatures (Andre, 2014).
This distinction of population medicine versus precision medicine is more
profound than might initially be surmised (Lyles, 2014; Khoury 2018). At the nexus of
population medicine and precision medicine is care that is currently driven by “standards
of practice” or “clinical practice guidelines,” which are used interchangeably in this study. Health care providers formulate clinical practice guidelines based on individual and collective experiences in treating a specific disease or circumstances (Institute of
Medicine, 2011). For some disease interventions a profession-wide standard of practice
emerges quickly upon the availability of a new therapeutic, vaccine or procedure. The
pace of the evolution of a standard will depend on the degree of urgency and the
persuasiveness of evidence of safety and efficacy associated with the intervention
(Madhavan, 2018).
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While the existence of universal standards of practice do not exist for all situations – and even when they do there is flexibility for individual judgement and change in response to new developments – such frameworks provide a level of confidence from the practitioners’ point of view and assurance from the patients’ point of view (Institute of Medicine, 2011). This protocolization of care is a triumph for modern medicine, but it is built on presumptions of genetic or physiological conformity in populations. It serves well but the emergence of precision medicine is challenging the fundamental assumptions upon which clinical practice guidelines are based, particularly with respect to patient-specific decision making (Khatry, 2018).
To put a finer point on the above assertion, medicine is transitioning from a regimen of population-wide standards to a milieu of patient-specific diagnosis and treatment strategies. Toledo (2012) characterizes this disruption towards predictive medicine as technologically driven wherein a better understanding of both genomics
(interdisciplinary field of biology focusing on the structure, function, evolution, mapping, and editing of genomes -- an organism's complete set of DNA, including all of its genes) and the individual epigenetic response to the environment (that arising from nongenetic influences on gene expression) informs clinical strategy. In particular, at a cellular level there are modifications that can be analyzed by a series of “omics:” genomics (as defined above), proteomics (large-scale study of protein interaction), transcriptomics (set of
RNA transcripts that are produced by the genome), metabolomics (interactions of small molecules within a cell) and lipidomics (lipid profile within a cell) which together allow prediction and targeting of disease (Chen, 2013).
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The use of genetic polymorphisms (difference in DNA sequences among individuals, groups, or populations) has been enabled by low cost genetic sequencing.
Whereas the first genome sequenced was a product of the Human Genome Project at about $1 billion over a dozen years, today, sequencing can be completed within a few days at a cost of less than $1000 which will drop even more sharply over the coming years (Ginsburg, 2018). This technological development has occurred in parallel with advanced information processing and artificial intelligence that now allow the capture and analysis of vast amounts of data from an individual genome to a vast array of clinical trial data (Park 2018). The resulting understanding of disease pathophysiology has rendered the International Classification of Diseases (ICD) as functionally obsolete going into the future. The National Research Council (2011) has proposed a new taxonomy known as the Knowledge Network of Disease that integrates clinical information and research data structured under the “omics” described above for individuals and specific populations. This development is another example of how a clinical infrastructure supporting the precision medicine paradigm is underway.
Psychiatry research, by way of illustration, has demonstrated that in a stressful environment, epigenetic alterations (a heritable change that does not affect the DNA sequence but results in a change in gene expression) in the hypothalamic-pituitary- adrenal axis can modulate the stress response, a factor in post-traumatic stress disorder
(PTSD). Insight into epigenetic modifications to the same gene makes it possible to approach treatment of people living with PTSD while taking into consideration their unique disease mechanisms (Ressler, 2018).
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A further example is the engagement of this author in tissue engineering and regenerative medicine research that also intersects with precision medicine, including
“organs-on-a-chip” and personalized stem cell therapies. The former is used to study the
effect of experimental pharmaceuticals during safety and efficacy testing at animal stages
thereby avoiding ethical issues raised by animal experimentation. Moreover, the creation
of organs-on-a-chip allows testing drug therapies in the lab before administering clinical
treatment. Using a patient’s own stem cells allows creation of a patient-specific organ-on-
a-chip to study how different drugs act on the patient’s own tissue (van den Berg, 2019).
There is an overriding concern within the public health community and among
medical ethicists that precision medicine will exacerbate health inequity between the
developed and developing worlds (Dankwa-Mullan, 2015). This is a legitimate concern but there are emerging ways that precision medicine can establish a groundwork for a more just international health regime. By way of example, algorithms for disease prediction and treatment can be based on a subpopulation-specific set of characteristics, such as genetics, drug responses, lifestyles, and social demands. This is a massive amount of data that can be integrated from medical centers globally. To drive this research, the
National Institutes of Health (NIH) announced, in 2015, the Precision Medicine Initiative
(PMI), a program for delivering resources to projects aimed at creating new methods to improve health care by applying technologies that maximize effectiveness by taking into account individual variability in genes, environments, and lifestyles. The related initiatives are administered on a global basis through governmental and philanthropic grants thus laying the groundwork for a more rapid integration of precision medicine
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among developing countries once they are ready and have the requisite clinical
infrastructure.
Interestingly, the concerns in the West regarding these developments are shared
universally, i.e., concerns related to consent, confidentiality, and intellectual property
(Fiore, 2016). These databases must be structured and administered considering ethical
concerns when giving access to different clinicians and researchers internationally while
protecting patient information from third party interests, as well as protecting the
intellectual property of the scientist or clinician who collects the data. While there are cost and human resource constraints for building a genomics complex in the developing world, this author, among others, is developing mechanisms, such as Rift Valley
Genomics in East Africa to lay the groundwork for benefitting populations in the developing world.
Literature Review
Precision medicine has captured the attention of numerous investigators over the
last 15 or so years resulting in the quantity of peer-reviewed journal articles, books and pieces in trade or popular press as described above. The literature, however, is almost
entirely in the medical and scientific corpus. Virtually no publications were discovered in the academic business literature addressing precision medicine or using it as case material or examples except for a book published by the National Bureau of Economic Research
(Berndt et al, 2019) on the economic aspects of precision medicine. Otherwise, precision medicine has not made its way into strategic, operational, marketing, or financial scholarship at present. Study 2 will further explore the literature as it relates to concepts that might be indirectly applied to precision medicine, for example, organizational
Page 49 | 477 theories on resistance to change or development of clinical practice guidelines. For purposes of Study 1, summarizing the articles produces a technical, medical compendium of issues. For current purposes, the literature breaks into the following categories:
Table 3: Representative examples of publications by category (see references for complete citations)
Category Sources Fundamentals of precision Akhmetov, I. & Bubnov, R. (2015) medicine Alyass, A., Turcotte, M. & Meyre, D. (2015) Andrey, F (2014) Annas, G. & Elias, S. (2015) Armstrong, K. (2017) Aronson, S. & Rehm, H. (2015) Bertier, G., Carrot-Zhang, J., Ragoussis, V., & Joly, Yann. (2016) Bishop & Varmus (1982) Chen, R. & Snyder, M. (2013) Cullis, P. (2015) Dhawan, D. (2017) Drew, L. (2016) Drews, J. (2000) Gronowicz (2016) Hamermesh (2016) Hays (2017) Hizel (2017) Hunter (2015) Johnson (2017) Kaur (2017)) Knowledge@Wharton (2016) Lemay (2017) Lopez-Correa (2018) Love-Koh (2018) Maggi (2016) Park, S. (2018) Patrinos (2018) Pothier (2017) Rahm (2017) Schulman (2009) Senn (2018) Sharma (2017) Sheingold (2014) Subbiah (2017) Trent (2012) Van den Berg, A. (2019) Willard (2017)
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Table 3 Continued Category Sources Application of precision Bartlett, G., Dawes, M. Nguyen, Q. and Phillips, M.S. (2017) medicine to a disease Berman, J. (2018) category Goldstein, I. (2012) Issa (2019) Katsanis (2017) Levit (2019) Nadauld, L. (2018) Prasad (2016) Quianzon, C. (2012) Ressler, K. (2018) Tannock (2016) Precision medicine in Aronson, S. & Williams, M. (2017) clinical decision making and Barker, R. (2016) companion diagnostics Blasimme, A., Fadda, Marta., Schneider, M., & Vayena, E. (2018) Cerrato, P. & Halamka, J. (2018) Chow, N. (2018) Dhawan, D. (2017) Hamermesh (2013) He (2015) Masys (2013) McCarthy (2017) Orlando (2017) Whirl-Carillo (2012) Wishart (2016) Adoption of precision Aspinall, M. & Hamermesh, R. (2007) medicine into Cooke, B., Worsham, E., & Reisfield, G. (2017) practice/standards of Davis, A., McKee, A., Kibbe, W., & Villaflor, V. (2018) care/clinical practice Graham D., Harrison, M., & Brouwers M. (2003) guidelines Grimshaw (1995) Grol (2001) Kinney (2004) Kredo (2016) Linskey (2010) Moffet (2011) Proehl (2012) Rosenfeld (2009) The Lancet Oncology (2017) Woolf (2012) Wright (2007) Policy and regulation- Ashley, E. (2015) oriented articles Berwick (2008) Cooper, D., Mitropoulou, C., et al. (2018) Dana, G. & Prichep, E. (2018) French (2017) Haga (2017) Hamburg (2010) Jenkins (2017) Kerali (2018) Mansfield (2017) Munshi (2017) Pregelj, L. (2017) Rai (2017)
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Table 3 Continued Category Sources Precision medicine and Bartlett, C. (2017) public health/globalization Bayer, R. & Galea, S. (2015) of precision medicine Bowen M. (2012) Dowell, S. (2016) Ginsburg, G. (2009) Khoury, M. (2011) Khoury, M. (2015) Khoury, M. (2016a) Khoury, M. (2016b) Khoury, M. (2018) Levy-Lahad, E. (2015) Lyles, C. (2018) Marzuillo, C. (2014) Molster, C. (2018) Park, S. (2009) Rezaie (2008) Rychetnik, L. (2002) Senier, L (2018) Sirisena (2018) Verma (2017) Ward (2017) World Economic Forum (2018) Commercial implications of Abrahams, E. & Eck, S. (2016) precision medicine Baden-Fuller (2013) Burns, L.R. editor. (2012) Cockburn, I. (2004) Danner, S., Solbach, T. & Ludwig, M. (2017) Das, R. (2017) DiMasi, J.A., Grabowski, H.G., Hansen, R.W. (2016) Ethical issues in precision Dankwa-Mullan, 2015 medicine Dumitrescu, R.G. (2017) Fiore, R. (2016) Gostin, L (2001) Joyner, M. (2015, 2019) Juengst, E. (2012, 2018) Lin, J-Z. (2017) Rodriguez (2017) Trusheim (2007) Ward (2012) Wynn (2018) Economics literature Arrow, K. (1963) Berndt, E., Goldman D. & Rowe, J. eds. (2019) Chandra, A., Garthwaite, C., Stern, A.D., (2018) Dubois, A. & Dube, M-P. (2018) Fragoulakis, V. (2015) Ginsburg, G. (2018) McDonough (2017) Mpitsakos (2018) Paci (2009) Pauly (2019) Reed (2017) Stern (2017) Towse (2017) Waldman (2012) Page 52 | 477
Table 3 Continued Category Sources Paradigm shift with Avruch-Black, K. (1987) relevance to precision Burton, J. (1986) medicine Bussard, A. (2005) Bird, A. (2018) Casti, J. (1989, 2000) Carlson, EA, (2018) De Anguloa, J. (2015) Goldstein, J. (2012) Gray, J. (2013) Halloran, S. (1984) Hyman, M (2004) Jewson, N. (2009) Monroe, K. (2001) Politi, V. (2018) Portin, P. (2015) Rose, N. (2013) Sawyers, C. (2009) Song (2017) Tang, P. (1984) Vegter, M. (2018) Willis, W. (2000) Institutional and Process Breton, M. (2014) Theory (Study 2) Dacin, M. (2002) Faigley, L. (1986) Jewson (2009) Kukk, P. (2016) Wells, R. (2001) Williams (2017) Strategy literature consulted Agarwal, R., Tripsas, M. (2008) for Study 2 Argyris, C. (2003) Amit, R. & Zott, C. (2001) Bojovic, N.M., Sabatier, V. & Rouault, S. (2015) Chesbrough, H. (2009) Chesbrough, H. & Rosenbloom, R. (2002). Organizational change Armenakis, A. & Bedeian, A. (1999) literature for Study 2 Avruch-Black (1987) Battilana, J., & Casciaro, T. (2012) Bazzoli, G., Dynan, L., Burns, L., & Yap, C. (2004) Bloom, S. (1988) Burke, W. (2018) Dacin, M., Goodstein, J., & Scott, W. (2002) Gersick, C. (1991) Kotter (2012) Landaeta, R. (2008) Lukas (2007) Lorenzi, N. (2000) Matthews, B. (2016) Macfarlane (2013) Narine (2003) Ozdemir, G. (2007) Sheldon, A. (1980) Waddel. D. (1998) Weiner (2008, 2009) Zucker (1987) Page 53 | 477
Precision Medicine Evolution
Dueling Business Models in the Health Care Value Chain
For the implementation of precision medicine there are implications that require
planning and reconciliation of the business models of the three participants in the health care milieu: providers (physicians, health professionals, hospitals, clinical laboratories, other facilities), producers (pharmaceutical, biotechnology, medical device and other developers and manufacturers), and payers (the managers – governments, insurers – of pooled risk reserves for the reimbursement of health care costs. The necessary reconciliations will begin with producers, specifically the biopharmaceutical industry.
Impact of Precision Medicine in the Context of Pharmaceutical Development
Most biopharmaceutical companies currently pursue strategies surrounding precision medicine but the pace of adoption of the principles of precision medicine over the last 20 years suggests that a consensus as to standards of practice and integration of biopharmaceutical products into therapeutic strategies is a work in progress. As a reference point, over the last decade the number of precision medicines under approval by the US Food and Drug Administration (FDA) increased from five in 2008 to a total of
145 in 2018 (Personalized Medicine Coalition, 2018; Appendix B). Another nearly 120 precision medicine products are in development across all phases of product development as monitored by the FDA (Citeline/Pharmaprojects Data, 2019; US FDA; Appendix D).
To put this growth in activity into the larger picture of biopharmaceutical development, the Synthetic Period provided clinicians with diagnostic tools that allowed accurate determination of disease states in infection and inflammation, the cancers, the
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underlying causes of heart disease such as hypertension and cholesterolemia, and
metabolic diseases such as diabetes. The Synthetic Period, more importantly, provided
broadcast interventions across the spectrum of disease using pharmaceuticals that had random effects of curing or alleviating disease based on the alignment of a medicine with how disease presented in a population. By focusing on aberrant cellular or metabolic-
process targets implicated in disease, pharmacy produced an inventory that addressed
hundreds of diseases. As described earlier, through the late 20th century, the entire global
armamentarium of pharmaceuticals was directed at approximately 483 cellular and
metabolic disease targets (Drews, 2000), i.e., the cumulative product of a century’s worth
of drug discovery was based on a relatively small library of disease targets. The tools of
molecular medicine now produce hundreds of new candidate targets per year (Sammut,
2012). In those cases where a physician had an armamentarium of several medicines that could be directed at a disorder, trial and error often provided a successful outcome over time. The Synthetic Period has produced approximately 2500 pharmaceutical classes approved by regulatory authorities during its century-long history, most of those over the last 70 years, or approximately 30 approved new medicines per year (FDA, 2019).
The Molecular Period similarly provides clinicians with diagnostic tools, but these target molecular characteristics of a disease as they present in patients individually.
The Molecular Period has provided approximately 1200 medicines since the first approvals in 1980, an average annual yield similar to the productivity of the Synthetic
Period during that time period. Generally, the Molecular Period has allowed interventions into previously untreatable and rare diseases or has replaced synthetic pharmaceuticals in selected clinical indications (FDA, 2019).
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Over the last decade, the biopharmaceutical industry has begun to provide
“precision” medicines that target the unique characteristics of a patient and their disease.
This study includes 145 approved precision medicines approved since 2010, or
approximately 15 per year, representing one-third or more of the approved new
pharmaceuticals during that period (Personalized Medicine Coalition, 2018).
The number of precision medicines and associated companion diagnostics in the
pipeline of US Food and Drug Administration (2019) approval process exceeds 200
(Appendix C), suggesting that over the next 10 to 15 years, upwards of half of
pharmaceutical productivity will be precision medicines. Thus, although a subset of each
of the outputs of synthetic and biological pharmaceuticals, it can rightly be claimed that
the industry and medical practice have entered the “Precision Period.” Presumably, the
Precision Period has been or will be embraced by the medical community over an
unpredictable but not immediate time frame.
The Producer Dimension: from Broadcast Blockbusters to Narrowcast Targets – Historical Forces Affecting the Evolution of the Pharmaceutical Industry
A retrospective review of the technological, social, and economic forces that have driven the biopharmaceutical industry over the last 85 years suggests that the emergence of precision medicine was essentially inevitable, but that a shift from the Synthetic Period to the Molecular Period was a prerequisite. In the larger argument of this dissertation, that inevitability should contribute to a sense of urgency for the adoption of the precision medicine paradigm. Technological inevitability, however, does not lead to inevitable adoption in practice. This dissertation provides an abbreviated history of the biopharmaceutical industry as it relates to precision medicine in three phases beginning
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with its 19th century origins, its middle period from approximately the Second World War
to the dawn of the biotechnology sector circa 1980 and the contemporary period that is
characterized by intervention in rare and genetic diseases. These three sub-periods are
characterized by this author respectively as illustrated here:
Period Sub-Period/Phase Circa Synthetic Serendipity 1820 – to present Suggestive Rational Design 1935 – to present Molecular Molecular/Genomic 1980 – to present Figure 1: Author’s summary of periods and phases of pharmaceutical history (in Figures 2, 3, and 5
Medical practice has accommodated to the availability of new medicines over
time as standards of practice emerged and evolved for any new therapeutic intervention.
While urgent social conditions sometimes abbreviated the period of adoption of a new
medicinal technology, e.g., in the Introduction the aforesaid adoption of polio vaccines and cyclosporin-A in organ transplantation, other new products had a longer period of gestation or substitution and in each instance, antecedent conditions for adoption were identified and debated, ultimately resolved, and an acceptable standard of practice emerged, generally from the appropriate specialty community of practice. Urgency, compelling data and clinical literature, and the magnitude of demographic need defined the time frame for adoption of therapeutics or technologies. Will the implementation of precision medicine follow a similar path? We can look to history for guidance.
Throughout the long first phase of pharmaceutical history, physicians were generally satisfied with the availability of any safe therapeutic intervention, even if individual efficacy had to be determined by trial and error and was not universal for their patients. This can be viewed as the Serendipity Period of “broadcast” medicines and it
Page 57 | 477 extended through the second historical phase – Suggestive Rational Design Period – with refinements driven by the emergence and evolution of pharmaceutical regulation. The imperative was to find interventions or vaccines, particularly for communicable diseases and large-scale common disorders like hypertension, cholesterol management, and metabolic regulation, such as in diabetes – conditions that affected nearly entire populations. Medical practitioners and the industry gradually discovered, however, that there was a scientific diminishing returns embedded in this strategy. The science did not allow the specificity necessary to manage illnesses reliably and thoroughly.
Put colloquially, the disease orchard of low-hanging fruit was largely picked over by the 1990s. The remaining opportunities were hidden in the high branches and spread out within the foliage. In other words, a more precise approach was needed to address the underlying biological characteristics of disease on the one hand and the genetic basis of disease on the other. The depletion of broadcast opportunities, fortunately, emerged just as modern biology elucidated the molecular and genetic basis of disease which characterize the Molecular Period. The new opportunities required a re-thinking of the fundamental business and revenue models of the industry which were based on broadcast products.
Since 1980, pharmaceutical science has witnessed a transformation of the broadcast commercial model initially to a narrowcast model and most recently to the
Precision Paradigm which is more than a model and is a function of the molecular revolution. The implications surpass the concerns of the biopharmaceutical industry alone and challenge the entire practice of medicine whether it be the legacy practices of
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developed world medicine or the evolving health care services in the emerging and
frontier markets.
How will the required changes be manifest in these two geographic theaters of
human need? What are the antecedent conditions in each? Where are the challenges
common? Where do they diverge? These important questions related to global health
equity are beyond this current inquiry but should be addressed in future research built on
this dissertation.
Historical Capsule of Medicinal Discovery: the Inevitability of Precision Medicine
Figure 2 illustrates the early history of pharmaceuticals. This Serendipity Period
includes the colorful “Patent Medicine” shows of the 19th century, but more importantly is
the period of origination of the most commonly known companies today such as Bayer,
Figure 2: First or “Serendipity Period” of pharmaceutical discovery and industrial development. Source: Adapted from Ravina, 2011.
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Merck, Lilly, and others. During this period of discovery enablement, the biological basis of disease was emerging and experimentation with chemical tools was applied to the fundamental insights into disease. The real rise of scientific pharmacology emerged during
the period between the two world wars. By this time, chemistry had come into its own as a
source for discovery, synthesis, and production, and led the way to a wide array of
therapeutics (Munos, 2009).
Discovery was based on molecular approaches to medicine and finding specific
disease targets that a natural or engineered chemical structure could affect. Figure 3
illustrates the second period of modern pharmaceutical history – the Suggestive Rational
Design Period. The second period of the pharmaceutical industry endures to this day in that
companies will embrace opportunities to discover and develop broadcast products. In
Figure 3: The second period, “Suggestive Rational Design,” of pharmaceutical discovery and development characterized by growing sophistication in chemistry married to greater insight into the underlying biology of disease allowing more specific chemical structures to engage with disease targets. Source: Adapted from Ravina, 2011. Page 60 | 477
current times, a quarter or more of all innovative pharmaceutical discovery and development is still comprised of the approaches identified in Figure 3 (FDA, 2019). It was during this period that the full-integration business model of the pharmaceutical industry emerged and stabilized. This model is represented in Figure 4. Note the linear, iterative characteristics of
Figure 4: The pharmaceutical industry value chain, inputs, and outputs during phases one and two of the industry’s history. Author’s interpretation of Burns (2002). the model in Figure 4. This illustration captures each of the dimensions of a company’s activities and capabilities. Historically the pharmaceutical business model, therefore, was built on full integration across the value chain.
From the second period until the present day this model as represented in Figure 4 has effectively remained unchanged except for the experimentation by the incumbent pharmaceutical companies with out-sourcing through collaboration for some of the links in the value chain. For example, there has been a heavy reliance since approximately 1980 on two factors: outsourcing, licensing, and acquisition of younger biotechnology companies; and on academic research providing the basis of discovery for new products. Academic sources were also the basis for the formation of integrated and virtual biotechnology companies in the thousands. (AUTM, 2019). This reliance was enabled in part by the
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passage of the Bayh-Dole Technology Transfer Act that year which allowed universities to
own and out-license inventions that originated with publicly funded research.
Industry captured discoveries made in academia though collaboration and in-
licensing (Munos, 2010). While this broadened possible sources for new products, the
industry still had to validate the discoveries made by the institutions and shepherd the related products through the highly regulated development process. The industry became further virtualized along the value chain through out-sourcing discovery and development to the emerging biotechnology industry. The incumbents could not rely entirely on the biotechnology companies to bring new products through the full regulatory phases, but it did allow the incumbents the opportunity to develop portfolios of hundreds of projects compared to the mere dozens they could manage internally (Munos & Chin, 2011). The
“real-options” model of decision making, therefore, was superimposed on the traditional pharmaceutical business model, especially at the discovery phase (Gunther McGrath &
Nerkar, 2004; Hartmann & Hassan, 2006).
The difference between the Serendipity and Suggestive Rational Design Periods of pharmaceutical history is the rise of biologicals or large molecule medicines. This distinction between large and small molecules is a critical dividing point and is illustrated in detail in Figure 5. Until approximately 1980, virtually all therapeutics, except for some vaccines, were based on small molecules of a molecular weight less than 500 (the molecular mass of a given molecule measured in unified atomic mass units). These small molecules are easily absorbed into the body (Jungmittag, 2000). They are discovered either though natural product screening or through the design of a chemical structure tested for efficacy against a disease target. Such targets typically include the membranes of an offending
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Figure 5: The third period, “Molecular/Genomic,” ushered in the biopharmaceutical industry and drove development and the transition of targeted molecular specificity of a pharmaceutical to genomically driven precision medicine. Source: Adapted from Ravina, 2011; Author’s observations.
pathogen, cancerous cell, or the interference (“antagonist”) or promotion (“agonist”) of a
cellular or metabolic process.
While there are many estimates of how many therapeutic candidates must be tested
through all phases of development to produce one safe and effective molecule, the
consensus is about 10,000 thus indicating a costly and inefficient process (Waring, 2015;
DiMasi, 2016). Even with this logarithmic attrition, molecules that survive the development
process still suffer from a lack of specificity or precision as demonstrated by side effects and
adverse reactions associated with virtually all approved medicines.
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The industry has experimented with scores of management strategies to improve the
yield and lower the cost of therapeutic discoveries (Quirke, 2009). While this is a
fascinating scientific and business history and has implications for the industry’s business
model evolution towards precision, such history is not a focus of this study.
Based on advances in molecular and cell biology dating back to the mid-1930s, science progressed to allow the creation of new therapeutics based on biologic systems. The biotechnology industry emerged in the mid-1970s with a focus on biologically derived pharmaceuticals. The capabilities of producing such products by 1980 were the result of scientific developments from 1940 onwards, and while some of these capabilities were resident in the established small molecule pharmaceutical companies, there was a paradigm and investigative power shift to the biotechnology companies (Roijakkers, 2006). The biotechnology companies focused on small portfolios of potential products and would usher in new methods and criteria for product development and regulatory approval.
A foundational assumption of biotechnology was that its products would navigate a simpler and less hazardous regulatory pathway because their products mimicked naturally occurring materials. In contrast, small, synthetic molecules often lacked cellular specificity and ran the risk of toxicity (Sapienza, 2001).
The traditional or “incumbent” pharmaceutical companies responded to the emergence of the biotechnology and large molecule revolution in several ways (Wang,
2014). Incumbent pharmaceutical companies established in-house capabilities for conducting biotechnology research and development but did not have a comparative advantage in doing so, other than financial resources to fund internal research (Smith, 2011).
Furthermore, this shift in discovery tactics and infrastructure created cultural stress in the
Page 64 | 477 research and development organizations between the traditional medicinal chemists and the biologists. For example, during the 1980s, SmithKline Beckman – on the strength of the profits from its flagship peptic ulcer treatment – cimetidine (the first billion-dollar molecule) undertook to replace most of its small molecule discovery and development capacity with a biotechnology-based discovery program. While this strategic move could be justified scientifically, the refocus of research capability derailed development of small molecule products leading to a dearth of approvable new products by decade’s end (author’s observations while an executive at SKB). Consequently, SmithKline Beckman underwent a series of mergers and consolidations in a quest to strengthen its product pipeline until it merged with Glaxo to form GSK Pharmaceuticals, Ltd. in December 2000. The irony here is that Glaxo’s molecule, ranitidine, was the principal competitive molecule with SmithKline
Beckman’s cimetidine.
Incumbent pharmaceutical companies moved towards in licensing the products produced by biotechnology companies through intellectual property and marketing alliances. Oftentimes, these relationships involved the conveyance of cash to the biotechnology companies through research contracts, license fees or equity investments from the pharmaceutical companies (Ratti, 2001). These relationships generally were for products that fit into the traditional call-patterns of the sales force and that could be administered in conventional clinical circumstances (Cockburn, 2004) and under prevailing standards of practice.
Alternatively, the pharmaceutical industry was on the alert for biotechnology products that could disrupt their franchises in disease treatment that involved small molecule therapeutics. In other words, these early products of biotechnology resembled the products
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historically sold by the traditional pharmaceutical industry. By way of example, the first
approved biotechnology product was recombinant human insulin. The human insulin gene
was recreated in 1978 and developed and produced by Genentech but rights were licensed to
Eli Lilly which substituted this new product for the porcine-based insulin supplied through
its existing franchise (since 1923) for diabetes care after FDA approval in 1982 (Quianzon,
2012). Similarly, new medicines based on monoclonal antibodies (MAbs) could be prescribed and administered for chronic diseases or needs in ways that did not disrupt traditional small molecule approaches to patient care (Liu, 2014).
Incumbent pharmaceutical companies generally acquired biotechnology companies when products were in late stages of development (Phase III clinical trials) or after one or more products is issued New Drug Approval (NDA) status (Burrill & Company, 2011). This
was, however, not universally true. Incumbent companies often acquire early stage
biotechnology companies long before their products were approvable (Gambarella, 1992).
Such action was deemed necessary when the biotechnology company had a potentially
disruptive therapeutic or a technological platform for discovery or production. The target
companies were typically fully integrated into the operations of the acquiring company or
sometimes allowed to function semi-autonomously.
Two noteworthy examples are the acquisition of Genentech by Roche which was
phased over the period of 1990 to 2009 but remains relatively autonomous operationally.
More recently, in 2011, Gilead acquired Pharmasset, a publicly traded company at the time,
as its products were nearing FDA approval. Doing so provided Gilead with a new
therapeutic for the cure of Hepatitis C, a successful but extremely expensive therapeutic
priced at about US$ 80,000 for a full treatment course.
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The fourth type of relationship that has emerged occurs when a pharmaceutical
company forms an alliance with either an academic health center or a biotechnology
company engaged in development of a gene therapy protocol with associated gene-delivery vectors, or an immunologic approach to treating cancer, often referred to as immuno- oncology. An example of the latter is the August 2012 alliance by Novartis and the
University of Pennsylvania aimed at bringing a new, personalized immunotherapy approach
to patients with a wide variety of cancers. Five years later this alliance resulted in FDA
approval for the chimeric antigen receptor cell therapy (CAR-T) branded Kymriah™
(tisagenlecleucel, formerly CTL019) for the “personalized” treatment of advanced acute
lymphoblastic leukemia (ALL). The uniqueness of these clinical strategies is based on the
engineering of a patient’s own cells in a laboratory or the precision customization of genes
to be infused into the patient’s cells. Gilead has also entered the realm of gene therapy with
its 2018 acquisition of Kite Pharmaceuticals.
While gene and cell therapies might not seem a dramatic departure from traditional
administration of a medicine, they share little in common historically because the processes
are not based on mass production of products with an extended shelf life. Moreover, while
these therapies target life-long diseases or life-threatening diseases, they are generally
administered once or merely a few times to effect a cure. Consequently, these therapies are
expensive to develop, customize and administer often requiring pricing at hundreds of
thousands of dollars and close collaboration between the pharmaceutical or biotechnology
producer and the providers of care. Historically, there has been an arm’s length relationship
between producers and providers. These new technologies have led to a new era of precision
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medicine which is challenging that relationship and has become the essence of the revolutionary pressures on the traditional pharmaceutical business model.
A Conceptual Model based on Technological Forces Combined with Commercial and Social Forces
The reasoning and fact pattern over the last century suggest a conceptual model of
how drivers of change in pharmaceutical development arise and how the industry evolves
accordingly. Given the level of understanding of biology from the 19th century into the
mid-twentieth century and the available investigational tools, the industry could not
provide the medical community with anything more than broadcast therapeutics –
essentially a one-size fits all interventional model. As described earlier, this broadcast
armamentarium was beneficial but had inherent limits in its clinical depth and
demographic breadth. As cited above, by the year 2000, for example, the global inventory
of pharmaceuticals was directed at only 483 therapeutic targets divided into seven
biochemical classes of medicinal targets, including cell surface receptors, enzymes,
hormones and factors, DNA mutations, nuclear receptors and ion channels (Drews,
2000). While these classes represent specific targets, they are only early steps at precision
medicine.
As medicinal chemistry and biology developed in the mid-twentieth century, the
industry was able to produce medicines targeted to more specific indications. Once
competence in disease definition and staging increased, specificity with disease targets
emerged. Regulatory authorities kept pace by demanding greater specificity thus driving
a cycle to more and more precision. Targeted therapeutics – against cell membranes or
Page 68 | 477 receptors – was the platform for driving pharmaceutical science towards greater precision. To extend this metaphor, the application of molecular biology towards the replication of therapeutic human proteins through means of genetic recombination or monoclonal antibodies together with the insights provided by genomics were the scaffold on which precision medicine was to be built. Retrospectively, the drive towards precision medicine was inevitable as the conceptual model in Figure 6 suggests.
The scientific inevitability of precision medicine, however, was not to be matched by the immediacy of clinical adaptation or confidence in the inherent advantages offered.
Figure 6. Conceptual model illustrating the passage of therapeutic interventions from a broadcast business model through to a narrowcast model and ultimately a precision paradigm mediated by technological forces but resisted by organizational and professional inertia. Source: Author’s conceptualization.
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While there are different obstacles in established centers of medical practice versus
emerging systems of care, there are common elements that are explored in this study.
The Rise of Precision Medicine and its Implication for Pharmaceutical Company Relationships with Providers
Precision medicine is an “emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person” (National Institutes of Health, 2015). Its emergence has been accelerated by advances in genomics, biomedical analysis, and big data approaches to the life sciences.
Simply stated, precision medicine matches specific disease genetics (genotypes and phenotypes) with targeted large molecule medicines or other approaches such as gene therapy or cancer immunotherapy. Precision medicine brings complexities to care and will be inherently expensive during the decades of its introduction, but it is an alternative to the broadcast approach to the medical interventions developed over the last century
(NIH, 2015).
Pharmaceutical development coupled with clinical care is already an interdisciplinary endeavor, but precision medicine amplifies the complexity with entirely additional disciplines such as targeted molecular diagnostics, genomic analysis, and predictive modeling. This complexity introduces challenges related to stakeholder management and communication, surfeits of data, proliferation of costs for prevention and treatment, and a re-definition of value from a patient’s perspective. In short, there are profound implications for the pharmaceutical business model (Faulkner et al, 2012).
Moreover, it introduces additional diagnostic variables into clinical practice that might aggravate resistance to precision medicine by clinicians.
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The emergence of precision medicine, therefore, is the tipping point. The
incumbent pharmaceutical companies are the beneficiaries by merger or licensing of the
research of biotechnology companies and for many new products must adapt to a new
paradigm of care and reconfiguration of the health care value chain (Wang, 2014). That
model is a movement from the sale of a medicine alone to participation in a treatment
program. It is also a movement from developing medicines for broad application to a disease state to narrow targeting of eligible patients. Finally, the traditional producer -
provider relationship will give way to participation in care networks (Smith, 2017). Are
these factors the basis for a re-defined relationship between producers and providers?
The role of precision medicine in driving change has been accelerated by
President Obama’s Precision Medicine Initiative which allocated $215 million targeted
for new approaches to cancer intervention (White House, 2015). While the confluence of
technology brings about an inflection point for precision medicine, the major political
driver is rapidly escalating health care costs of which pharmaceutical costs are a part.
Indeed, as of 2016 the Tufts Center estimated that the costs of development and approval
for NCEs or NMEs is approximately $2.6 billion allowing for the cost of failed attempts
(DiMasi, 2016).
It is worth pointing out that these development costs are associated with
medicines intended to be broadcast to large populations. Precision medicine limits the
market for any particular medicine and absorbs additional costs in clinical administration
for genetic qualification and monitoring. Costs of precision medicine, therefore, cause
concern throughout the health care value chain. Moreover, the correlation of a given
medicine’s applicability to any given patient with any given condition, will be based on
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searches of data repositories vis-à-vis large biobanks of pathologic tissues and cells. The compilation and organization of these biobanks is an infrastructure that develops over decades or generations of care; the capability is not universally available at hospitals.
Monetization of that capacity will be an inevitable element of precision medicine (Ntai et
al, 2014).
Access to organized and curated biobanks will necessarily be part of the networks
that will enable precision medicine. What players, organizations and systems must be in
place to enable precision medicine? At the very least, the participants will be
pharmaceutical or biopharmaceutical companies in concert with academic health centers
or hospital systems that have developed the biobanking capability (Hsu, 2013).
Theoretical and Managerial Challenges to Implementing Precision Medicine: Producer Perspective
Arguably, there are decades of experience among companies in the industry in
forming necessary alliances for product development, but the history has been directed at
the development of broadcast pharmaceuticals for comparable populations of patients. As
patient groups are segmented clinically or genetically, economies of scale collapse
because the move is towards narrow-cast administration of a medicine. Moreover, there is
a new array of scientists and clinicians in the mix, either at the bedside or in laboratories
equipped to support the care team (Roijakkers, 2006). This new milieu requires innovation across an array of capabilities, but the foundation is necessarily a rethinking of business models for the industry (Sabatier, 2012).
Baden-Fuller and Haefliger (2013) define business models as “a system that solves the problem of sensing customer needs, engaging with those needs, delivering Page 72 | 477
satisfaction and monetizing the value.” Chesbrough (2010) posits that business models go
beyond activities of the firm but necessarily include collaboration with other
organizations for value creation and capture. According to Teece (2010) the goal is “. . .
the benefit the enterprise will deliver to customers, how it will organize to do so, and how
it will capture a portion of the value that it delivers.” There are four business-model
components, according to Baden-Fuller & Mangematin (2013): customer identification,
customer engagement, monetization and value chain and linkages. The concepts of
customer identification and engagement go beyond making a passive sale of goods or
services. In the context of clinical care, especially precision medicine, business model
innovation must go beyond traditional market analysis to engagement of physicians and
patients to formulate a patient-centric solution. This represents a bifurcated challenge to
both producers and providers, neither of which have participated in collaborations of this type.
The transformation of the pharmaceutical industry business model from its historical approach to formulating a broadcast therapeutic product to the development of comprehensive solutions based on in-depth patient engagement is revolutionary (Wang,
2014). The pharmaceutical industry lifecycle, like all others, had its period of emergence that set the stage for growth and maturity as the practice of medicine and social conditions caught up with what was available technologically. If biotechnology had not emerged by the 1980s, it is possible that the pharmaceutical industry of that era might
have begun a decline given the reduction in NCE small molecule approvals since that
time. Biotechnology was a reinvigoration of the industry, essentially back to its emergent
state following the second world war (Agarwal, 2008).
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The positive impact of biotechnology began abruptly as the incumbent
pharmaceutical companies quickly began a campaign of collaboration and in-licensing
with the new biotechnology entrants (Sabatier, 2010), a practice that continues to this
day. The strategy behind these strategic alliances, however, was to extend the traditional
business model by adding products that were analogous to the traditional small molecule
offerings. The global product pipeline of new medicines under development predominantly can support continuation of the traditional model for the foreseeable future. The shift, however, of the pipeline to a majority of biologicals, half of which require parallel genetic diagnostics to establish patient eligibility poses the necessity for business model innovation. Pharmaceutical and biotechnology alliances essentially allow the incumbents to out-source or access technological innovation. This sequesters the
incumbents from disruption of their business models (Pisano, 1988) and could be a
commercial drag on precision medicine.
Precision medicine, however, may be the harbinger of significant change as
providers and producers explore new, complex approaches to collaboration. There is a
risk, however, that the cognition or mental mapping of management of the incumbent
pharmaceutical companies will create a strategic inertia. Indeed, the work of Tripsas &
Gavetti (2000) in their examination of Polaroid demonstrated that despite heavy
investment in digital technology the management could not re-organize around a business
model that shifted from the razor-razor blade model of selling a capital good – a camera – with aftermarket consumables.
A task of this research, therefore, is to characterize organizational and professional obstacles to precision medicine and posit a framework for addressing strategic inertia. Or to Page 74 | 477
put a finer point on the matter, this study examines the nature of the pharmaceutical
industry’s response to the forces of change leading to precision medicine. The responses
range from a major departure from traditional models to a fine-tuning of the historical model in such a way as to preserve prevailing strategy but still access new product opportunities.
Curiously, the forces portrayed herein affect all companies in the industry in largely similar ways. Ultimately, are companies meaningfully responding and, if not, are there inertial factors that account for the resistance to change?
Convergence of Scientific, Commercial, and Social Forces
Kenneth Arrow observed in his classic essay “Uncertainty and the Welfare
Economics of Health care” (1963) that health care is different. The aforesaid social contract
that enables the existence and operation of the pharmaceutical industry also means that the
industry is different and that the forces that affect it differ from the forces that affect other
industries. The industry has a “higher calling” to participate in the triple aim of health care –
access, quality, and affordability (Berwick, 2008) – according to its privileges and
capabilities. It is within a maelstrom of forces that the industry’s business models and
dynamic capabilities evolve, and as they do, the efficiency with which the industry develops
and delivers its medicines ebbs and flows. Commercial and social change might not keep
pace with science and technology for reasons entirely dependent on organizational dynamics
or individual concerns. Human welfare hangs in the balance. And any sense of urgency for
adoption of new therapeutic strategies can lag, as is the case with precision medicine.
Consequently, this study now explores how the managerial challenges provoked by a
series of forces can respond strategically in the form of business model shifts and
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reconstitution of capabilities in order to adapt; the precision medicine paradigm is the
illustration. Responses by producers and providers have been aggressive in some cases and
nearly passive in others, urging the question as to why management acts as it does. While
this exploration might suggest a need for new theories of strategy and operations that are
particular to the interplay of health care producers and providers, there may be broader
implications for firms more generally, i.e., response to a Kuhnian paradigm shift.
To further illustrate the forces of change, this study will now survey the pre-1980 baseline of industry characteristics and then embark on a detailed historical analytic interpretation of major forces on both theoretical and pragmatic planes leading to precision medicine, thus further demonstrating the argued paradigm shift. Popular discourse about the pharmaceutical industry cites a variety of forces that have affected the financial performance, core strategy and business models over the last 35 years. For convenience, this study focuses on the following factors broken into three over-lapping categories: scientific, commercial, and social.
Health care is often viewed by academics as a grouping of silos. While convenient for analytical purposes, it fails to integrate factors that are truly interdependent. This is particularly true when viewing the forces that interrelate the underlying science, technological transformation and evolving clinical practices. Some of the critical factors confronting this triad of activity include a series of interlocking factors including scientific, clinical and demographic factors; commercial, competitive, financial, and pricing forces and social, economic, regulatory, and legal forces.
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Scientific, Clinical and Demographic Factors
There are a series of related factors across the categories of science, clinical and
demographics. The movement in clinical care from a physician-centric and fee-for-service driven medical environment to a patient-centric and outcomes-based reimbursement environment is a case in point that illustrates a convergence. Precision medicine is a key towards outcomes-based reimbursement. Moreover, there is a relentless trend towards
escalating costs of medicinal discovery research and especially clinical development with
higher probabilities of failure during development.
The selection of scientific pathways and the selection of projects has also witnessed
a movement towards open-innovation and a real-options portfolio approach to out-sourcing
the research function through strategic alliances to biotechnology and specialty
pharmaceutical companies. This decentralization of R&D to an out-sourcing model has had
an impact on knowledge management that has risen to the status of a major challenge for the
data-driven nature of precision medicine. In this environment, there was a dramatic loss of
revenue and associated profits – in the tens of billions -- when the “patent cliff” that the
industry tumbled over between 2009 and 2015 with the expiration of scores of patents, a
manifestation of the broadcast model in effect at that time (Vondeling, 2018). Precision
medicine replaces the emphasis on patents to exclusivity based on a variety of factors such
as targeted diagnostics and patient-specific strategies.
As a demographic backdrop, there is an on-going shift of the global burden of disease – irrespective of the COVID-19 pandemic that overshadows this writing – to non- communicable, chronic illnesses which presents market and revenue opportunities as well as
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scientific and public health challenges (Feigin, 2014; IHME, 2017). The role of precision medicine in cancer is preeminent, but there is also a role in other non-communicable disease as well as communicable disease. The numerous diseases left to be addressed, as well as those for which there are medicines that work but not optimally, do not invite “one-size fits
all approaches” to medicinal development. Rather, the biological challenges of the
underlying diseases must be addressed by specialty products which by their nature have
neither the unit volumes nor the associated sales to deliver the historical top and bottom
lines of the biopharmaceutical industry.
Commercial, Competitive, Financial, and Pricing Forces
All industries are subject to commercial, competitive, financial, and pricing forces.
Of course, the pharmaceutical industry is not immune to such circumstances but some
analysts would argue that, in fact, the pharmaceutical industry is immune to the full effects
of these factors because many of its practices are essentially subsidized by social investment
in basic life science, and that pricing is shielded by a price elasticity of demand resulting
from social policy, elaborate insurance and payment systems, and the general sentiment to
provide care and accompanying pharmaceuticals at all costs, at least in the US.
The above factors notwithstanding, the pharmaceutical industry has been challenged
by numerous factors affecting its underlying economics. These factors are far-reaching and include: increasing competition across all product lines and accelerated product life cycles; a shift of products from lower production cost small molecules to higher cost biologicals; an expansion of business lines across the health care value chain, i.e., convergence of producers and providers for some therapeutic interventions, particularly in oncology; a virtualization
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of activity wherein the corporations reduce fixed costs and experiment with various
approaches to out-sourcing key activities and resources; a convergence of ethical
considerations with pricing policies, especially as these affect access to medicines in
developing countries; and, globalization and the rise of the global health agenda also place
demands that the industry contribute to solutions for neglected tropical diseases at a time when anti-infectives generally are shunned as business lines (Bradley, 2007).
There are other self-inflicted wounds, such as divestment, especially during the
1980s of non-medicinal businesses, e.g., diagnostic laboratories, medical devices, laboratory
instrumentation, animal health, etc. in response to capital market demands for pure plays on
the superior margins associated with sales of medicines (LaMattina, 2011). Decades later, in
response to needed companion diagnostics in precision medicine, there is new investment in
non-medicinal businesses, particularly diagnostics and delivery system technologies, to
meet the requirements of new medicines (Kling, 2007). Finally, the use of social media to
supplement or supplant sales force detailing is changing the relationship with physicians –
the key customer. At the same time, social media is a factor that contributes to the building
of a base of patients with rare or genetic diseases by reaching these populations on a direct
to consumer basis (Greene, 2010). Social media and big data also track trends in disease and
demand, a foundational component of precision medicine.
Social, Economic, Regulatory, and Legal Forces
Pharmaceuticals and health care are among the most highly regulated industries and
are, therefore, sensitive to changes in social perception, the economy at large, and shifts in
the legal environment. Specifically, some of the factors at play in the industry are a steady
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deterioration of the esteem of the industry by the community at large, i.e., throughout the
20th century, the industry was consistently the most admired; today regard for the industry
has suffered catastrophically (McCarthy, 2019). Price pressures are exerted from all sides: by non-US governments that act as the payers for pharmaceuticals in their countries, or
Figure 7: The regulatory backdrop for precision medicine. Source: Author’s characterization adopted from representative schemata. other mechanisms of price control, as well as growing strength by private insurers and
Pharmacy Benefit Managers (PBMs) in the US in price negotiation.
Medicare does not negotiate pharmaceutical pricing which serves as a bulwark of stability in US pricing and provides the financial margins necessary to support medicinal discovery and development, but this too is under threat by the Trump Administration. Other government and legal factors arise from the increasing complexity of domestic (US) and
international regulations and higher hurdles for approvals. The regulatory environments and
requirements represent the most complex aspect of pharmaceutical development and must
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be modified for precision medicine oversight. While industries such as airframe
manufacturing, chemical processing, and others where the safety and environmental stakes
are high also have strict regulatory requirements, the pharmaceutical requirements of safety and efficacy presented in Figure 7 address the components of the phased regulatory process with their accompanying thought-frameworks.
Curiously, although regulatory provisions have evolved since the 1950s in the US, the foundational sequence is the same. This study does not assert that a radical change in the regulatory milieu would hasten or facilitate adoption of the principles of precision medicine into clinical practice but the question of whether the prevailing approach of Randomized
Clinical Trials (RCTs) is suitable for precision medicine, as opposed to say, Adaptive
Platform Clinical Trials, is an open question for regulators and the industry (Saville, 2016).
Other factors deepening the challenges of the current environment include international trade treaties and variations in the administration of patent law. There is also greater public scrutiny for clinical trial transparency and flexibility for compassionate use of pre-approval pharmaceuticals. Social media has also increased liability challenges and risk management needs. This is occurring in an environment of patient and consumer empowerment as a function of social trends that include patient participation in
“uncontrolled” social media reports on alternative treatment options and reports on adverse drug reactions not supported by science.
Together these forces compel a significant re-thinking of the pharmaceutical business model and the role of precision medicine in that model. From 1980 to the present time, there is overwhelming evidence that the pharmaceutical industry was responding to these changes through a re-consideration of its business model (PWC, 2019). The
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conventional wisdom is that these positive factors and negative factors do not balance and
that the overall forces on the financial welfare of the pharmaceutical industry is negative.
The scientific and investment hypotheses of the biotechnology industry (as opposed to the traditional discovery model that prevailed through the mid-20th century) are that
products would enjoy accelerated review through the regulatory process because the new
molecules in question were essentially natural, human products. While these products would
initially be more expensive to manufacture, costs would reduce as production reached
suitable scale. Margins would be protected through higher sales prices justified through
improved clinical outcomes and the emerging field of pharmaco-economics during the late
1970s. Based on the mix of synthetic products and bio-molecules that have been approved
over the last 15 years, it is reasonable to assume that the majority of major pharmaceutical
companies shifted the emphasis of their research – intramural and extramural – from small
molecules to large molecules either through re-structuring in-house capability, strategic
alliances or mergers starting in the early 1980s (Jones, 2002).
1980 as the Pivot Year towards Precision Medicine
Establishing 1980 as the historical dividing line towards the emergence of precision
medicine is somewhat arbitrary but is a good benchmark year. It is the IPO year of
Genentech and the year that Genentech announced the development of Humulin® or
recombinant human insulin (licensed to Lilly) and Protropin® or recombinant human
growth hormone. 1980 also marked the Supreme Court’s Chakrabarty decision which
enabled patenting of engineered life forms. The Bayh-Dole Act also became effective in
1980 and set-off an unprecedented era of university-industry collaboration and technology
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licensing. Finally, Congress passed the ERISA pension reform in 1978 which liberalized
investing in alternative assets by public and private pension funds. ERISA’s impact on the
availability of venture capital was first felt in 1980 and rapidly accelerated available funding
for the biotechnology industry. 1980 was also the first year that annual sales of a small
molecule pharmaceutical product reached $1 billion in global annual sales (Tagamet® or
cimetidine developed and sold by SmithKline & French for peptic and duodenal ulcers),
essentially re-defining for Wall Street an optimized gross margin target for the industry.
Cimetidine is among the first examples of rational design, receptor-based pharmaceuticals targeting the H2 receptor which mediated gastric acidity – the archetypal specific medicine of the Rational Design Period and a conceptual forerunner of precision medicine.
Foundational Thinking for Antecedent Conditions and Consequences for Precision Medicine
The pharmaceutical industry conventionally is assumed to respond to changes in the scientific, technological, clinical, and regulatory environment with alacrity.
This study does support the notion that the industry is accomplished at making tactical changes when driven to do so, but when its core business model is challenged, its tendency is to avoid business model change by taking tactics to extreme measures in order to preserve the status quo of its business model, a mindset hypothetically operative in delaying precision medicine proliferation.
In the matter of precision medicine, the tactical response of producers works as follows: by definition, precision medicine segments pharmaceutical selection to smaller population sub-groups. Although the commercial opportunity for these sub-groups
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approaches near total penetration once clinical use can be justified, the pricing of precision
medicine flirts with unprecedented levels, ostensibly to offset the loss of a larger market.
Equilibrium pricing will eventually be met, but at the present time, pricing of precision
medicines, especially with the added costs of diagnostics and the methods of physical
administration, are potentially obstacles to more rapid adoption. While general economic
conditions are discussed below, the pricing challenges of precision medicine are beyond the scope of this inquiry but the role of pricing vis-à-vis adoption is an area ripe for further research.
Figure 8 represents the ebbs and flows of thinking along the path to precision medicine. As many approved pharmaceuticals exhibited adverse reactions once introduced to large populations, regulators began to re-think clinical trial design. The
Figure 8: Dynamics of antecedent – consequent reconsiderations for precision medicine. Author’s depiction.
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final classical antecedent assumed that multiple trials would satisfy the desire to see
positive effects and provide for safety. This approach was consistent with broadcasting of
pharmaceuticals. A move towards individualized precision medicine necessitates a
modified approach. Table 4 builds on this revisionist approach to antecedents and
consequences with a focus on precision medicine.
Factors Suggesting a Paradigm Shift
Building on the discussion of Paradigm shifts in the introduction, Table 4’s configuration puts an emphasis on change; it sees pharmaceuticals as part of a dynamic care environment that necessitates a non-linear approach to formulation of strategy and ultimately a business model suited for precision medicine. This dynamic translates to the providers, as well. While Table 4’s descriptors may seem to be imbedded in the milieu of health care, they are there as a function of an idealized and rationalized view of the system. Adoption of precision medicine will require a radical rethinking of this process.
As characterized in the Introduction, from Kuhn it is possible to formulate four practical criteria or indicators of a paradigm shift that must be aligned so that they can be applied to organizational readiness and acceptance of a paradigm shift:
• Frames of reference or mind-mapping, i.e., insight into the new discovery and
acceptance of the new truths associated with the new way of thinking;
• Investigational activities, i.e., ways that research approaches have changed in
observable ways;
• Contribution to the new body of knowledge and approaches to validation;
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• Approaches to theory formulation and strengthening consistent with the new
paradigm, and whether those questions asked, the procedures followed, data
gathered, and means of analysis are appropriate to the model and metaphors of the
new paradigm.
Table 4: Reconfiguration of antecedents and consequences in the era of precision medicine. Author’s formulation
The bulleted factors above can be applied to the current circumstances of precision medicine vis-à-vis the industry in turn:
Paradigm Indicator 1: Frames of reference. The origins of “precision medicine” as a concept arose during the 1980s. Explication of the molecular basis of disease – itself a paradigm shift from the prevailing morphologic approach to pathology – had been in full force over a generation of research. By that point it was becoming clear that for many diseases, particularly neoplastic diseases or cancers, a patient-specific approach might be possible. As renegade divisions of a person’s own cells, cancer invites the possibility of
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“personalized medicine” theoretically driven by knowledge of genetics and mutations. At this time, the concept of the cellular origin of “retroviral oncogenes” introduced by
Bishop and Varmus (Bishop et al, 1982) was gaining currency. During the 1980s, geneticists postulated that the human genome could be mapped and sequenced.
That vision was achieved decades earlier than expected when the Human Genome
Project was launched in 1990 and completed in 2003. It was not clear before or during the project what advantages to medicine such an effort would bring, but there was chatter about the possibilities of “patient specific therapy.” As specific genes were identified and the relationship of variations in gene sequences to diseases and disorders were documented, the concept of personalized medicine, later dubbed precision medicine, emerged. Once genomic sequencing further converged with biomarker research, bioinformatics and big data analysis, the technological basis of precision medicine accelerated.
The expectation is that precision medicine will improve outcomes for those patients that qualify for treatment with specific medicines following genetic testing.
Improved response rates to therapies will reduce human suffering and the economic cost associated with ineffective treatment. Development costs will also reduce through smaller-scale clinical trials and reduced time-to-market. These possibilities have attracted investment by pharmaceutical incumbents, venture capitalists, and the public markets.
Apart from the scientific obstacles still to be overcome, how can the pharmaceutical industry organize around a business model to deliver the goods to a provider model still in its own state of flux? Challenges remain for the entire array of health care stakeholders. Precision medicine’s foundation is that patient populations can
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be stratified using biomarkers (a measurable indicator of the severity or presence of some
disease state) but this same stratification increases the difficulty of identifying trial
participants. If patient recruitment is achieved and the clinical trial is a success, the
product launch will be more clinically complex and will be characterized by a series of
partnerships across the spectrum of stakeholders, as described in Figure 9.
Figure 9: The stakeholder universe of precision medicine – a simplification of Table 2 in the Introduction. Source: Author’s characterization
Given that precision medicine has been taking shape over 30 years, important
questions are: “Is the science ready for clinical translation?” The legacy of biotechnology is
one of delayed or unrealized promises. “Is this time different?” “Is the industry ready?”
Figure 10 identifies the contemporary drivers of precision medicine.
Paradigm Indicator 2: Investigational activities. A common thread in the drivers of precision medicine is that each is data driven and characterized by a surfeit of information. Each of the stakeholders is inundated and needs systems capable of retrieving the appropriate information for the appropriate clinical or administrative service. Another definition of precision medicine is that it entails the systematic use of information for the optimization of a specific patient’s therapeutic intervention. In
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practice, how does precision medicine function differently from traditional care? Table 5
provides insight and examples.
Figure 10: Drivers of precision medicine. Source: Glorikian, 2013
It is worth noting in Table 5 – a specific depiction of Figure 10 – that for each of the enablers there is a closer, networked relationship with care providers as well as their own inter-relationships. This observation suggests, by way of example for diagnostics producers (Dx), that their business model is also subject to shift. Precision medicine will
drive diagnostics (Dx) to evolve as players add value to core products and services and
integrate these with data and analytic sources. The shift in the pharmaceutical or
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Table 5: Contrasting traditional and precision care.
Traditional versus Precision Health care: examples
Enabler Traditional Health care Precision Health care
Pharmaceutical/biotechnology Chemotherapy (e.g., cisplatin) for Pfizer’s Xalkori (crizotinib) for non-small cell lung cancer is non-small cell lung cancer is 80% effective less than one third of the effective with diagnostic time with severe adverse reactions. screening. Reactions are mild to The ratio of comparative moderate and the CE:C ratio is effectiveness to cost is moderate. high. Medical devices Traditional colposcopy for cervical DySIS colposcopy for cervical cancer is subjective and sensitivity cancer is objective with dynamic about 50%. The CE:C ratio is mapping of markers. Sensitivity is moderate. about 85% with a CE:C ratio of high. Diagnostics The PSA screen for prostate Genomic Health’s Oncotype DX cancer is sensitive 40 – 80% with For breast cancer has high specificity around 90%. CE:C sensitivity with >90% specificity. ratio is low with a low to moderate CE:C ratio is high for oncotype impact on therapy selection. Dx with high impact on therapy selection. Source: After Glorikian, 2013
biotechnology business models consider the use of companion diagnostics (Dx) to qualify patients for their medicines as well as integration with the data and analytic sources. In short, each of the stakeholders will expect the Producers to participate across the disease care process which includes prediction, screening and detection, diagnosis, and disease staging, theranostics and companion Dx, prognosis with outcome prediction and post-care monitoring.
Figure 11 illustrates the dynamic of integrating knowledge categories in precision medicine, all of which must ultimately be curated by the providers in concert with the producer.
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Figure 11: Brave new world of integrating knowledge categories to the care planning and business model process. Source: Compilation by author.
Paradigm Indicator 3: Contribution to the new body of knowledge and approaches to validation. This study has built a case that the pharmaceutical business model is entirely linear and iterative. The challenge for the industry in shifting its business model to the nature of precision medicine will have to move beyond the traditional, 80-year-old models of fully integrated and virtually integrated processes along the value chain. As seen in Figure 12 – the conceptual model for this research study
– producers and providers must apply a new logic that allows development and commerce from broadcast small molecule medicines and their analogs in the form of large molecule medicines that can be produced, packaged and administered similarly to their precursors, to complex, narrow cast biologicals that require a wider range of competencies necessary to develop and manage an individualized care plan. Such a shift necessarily involves a non-linear, non-iterative networking approach for the alignment with partners across the stakeholder and value chain spectra.
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Figure 12. From a linear product-centered to a patient-centric business model. Derivation and re-interpretation by this author from Bojovic et al, 2015 to illustrate business model impact of precision medicine.
Bojovic (2015) also derives implications for re-thinking business plans and models associated with precision medicine as displayed in Table 6. The framework is a useful approach to explaining and managing the resistance to precision medicine.
The conditions and framework for the formulation of a precision medicine business model have been established. The remaining task for this study is to explore how the role and sensitivity of the adoption and integration of precision medicine can be approached as a function of the development of standards of practice and whether the standards promote the reconciliation of business models among the providers and
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Table 6: Implications for re-thinking business plans and models associated with precision medicine. Section of Business Plan Recommendations for Producers and Providers Innovation Assessment The nature of precision medicine requires integration in both the research and development phases as well as in care delivery. The user value chain will expand on the basis of how the different stakeholders will interact (patients, providers, producers, and payers). Management Team Integrated management teams comprising decision-makers and enablers across the participating stakeholders, especially among producers (Rx and Dx) and provider teams (MDs, data analysts and genetic advisors). Market Research Market research requires value assessments across each stakeholder and for each stakeholder holds a complexity of choices. Conjoint analysis models will be necessary to design and introduce to the process. These models can play a role in clinical decision making. Competitive Analysis Reliance on intellectual property claims are likely to be minimized as precision medicine segments the patient populations, i.e., markets thus providing a wider suite of alternative therapeutic strategies. Business Model The interdependent nature of the stakeholders on the value chain requires re-thinking of the payer model, therefore, requiring modification of the biopharma business model. Precision medicine does not align with the traditional revenue model. Outcomes must be factored in; payers must be proactive rather than passive. Financial Projections Precision medicines are a milieu of activity involving producers and providers. Costs and revenues must be modeled accordingly. Re-interpretation of Bojovic (2015).
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producers. The approach to answering that question is described below. Study 2
will test these notions through a series of interviews with providers at different stages of
precision medicine operations.
Paradigm Indicator 4: Approaches to theory formulation. Again, this refers to
strengthening of theory consistent with the new paradigm, and whether those questions
asked, the procedures followed, data gathered, and means of analysis are appropriate to
the model and metaphors of the new paradigm. This indicator is a work in progress, but
the actual development and availability of therapeutics and companion diagnostics is
strongly suggestive that the biological basis or theories surrounding the Molecular/
Genetics and the Precision Medicine Paradigms have been incorporated into practice. The
inventory of progress in this regard will be persuasive when presented later in this
research and in the Appendices.
Why and How Organizations Struggle or Resist Precision Medicine
Despite the relentless pace of progress in product development by producers, the integration of precision medicine beyond oncology into prevailing standards of practice in primary care, infectious disease, metabolic disease, or mental health has been slow.
Even in oncology where the field is best equipped genomically and pharmaceutically, the
framing of precision medicine as a standard of practice has experienced only punctuated
progress. The implications of the modest responses to the availability of precision
medicine and other forces affecting the industry invite questions regarding factors that
contribute to medical practice and organizational inertia in the health care environment.
While development of a broad, robust theory of health care organizational inertia and
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change is a ripe area of investigation, this manuscript more modestly identifies the
obstacles in the adoption of precision medicine principles, establishes the antecedent
conditions for its adoption in countries with developed medical care systems, and
postulates implications for organizational theory. The factors described below will serve
as the backdrop for the exploration of organizational resistance to change in Study 2.
Characterizing the Obstacles to Implementation of Precision Medicine
As intimated above, research and development in precision medicine proceed
apace, but integration into clinical practice is relatively disappointing. The Personalized
Medicine Coalition has published (Pritchard et al, 2017) common challenges to adoption and has postulated strategies for countering these challenges. These factors were gathered though group discussions, surveys and interviews and then vetted in a national summit.
The process resulted in the categorization of five areas of need: education and awareness; patient empowerment; value recognition; infrastructure and information management; and ensuring access to care. The conclusion was that the transition to precision medicine requires parallel strategies. Interestingly, the data and discussions did not focus on the process of standard of practice consensus and development, and the need to reconcile the business models of the provider, producer, and payer stakeholders. This manuscript
supplements the prevailing literature by incorporating attention to standards of practice
and business model reconciliation to necessary components of an integration strategy, as
well as an investigation of organizational dynamics. Nevertheless, the foundations of
such a strategy are built on Pritchard et al, 2017. For purposes of a fuller context, the
Page 95 | 477 principles promulgated by the Personalized Medicine Coalition (PMC) are described here. These are the common challenges identified by Pritchard et al, 2017:
• Awareness and education: the equivocal terminology used to describe the field
of precision medicine, thus leading to confusion and uncoordinated efforts.
The result is low patient knowledge that suppresses demand for services and
associated products. Causal factors include the complexity of the underlying
science and difficulty in relating it to individual illness circumstances. In
short, there is a problem of communication to the public at large but even
within the community of health care providers. The PMC offers a litany of
solutions ranging from outreach through on-line education and social media,
formation of collaborative forums for unification of language, provider forums
convened for harmonization and communication of scientific and clinical
information, patient support groups within disease areas to acquaint people
with the opportunities, identification of community key opinion leaders
among providers, engagement of pharmacists as patient educators, and
updating medical and pharmacy school curricula.
• Patient empowerment. The challenge from the patient perspective is that
historically patients have not been optimally involved in treatment decision-
making or in overall policy development related to information privacy and
ownership, data protection and other ethical, legal, and societal issues. In
order to increase patient empowerment, the PMC advocates inclusion of lay
public in policy and protocols development related to such protections and the
use of information. Confidence must be built through cybersecurity measures
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for genomic information and the results of diagnostic testing. There is also a
prevailing pattern of misinterpretation and miscommunication of genetic-
based results requiring more advanced counseling services and guidance when
ethical dilemmas arise. Patient-experience and outcomes must be more widely
reported. Finally, the current clinical trials structure focusing on narrow
ethnicities and genders must be expanded ethnically and racially to provide a
broader range of therapeutic strategies better suited for patient groups.
Industry needs to develop and implement a health-care system-wide approach
to “basket-studies” and clinical trial enrollment based on molecular
characteristics.
• Value recognition. In the prevailing atmosphere, the majority of providers and
payers are not yet convinced of the benefits and practicality of precision
medicine because evidence of value is still emerging. This is a significant
problem with elusive solutions. Some concepts advanced include convening
payers with the diagnostic and pharmaceutical producers to formulate
technology assessment processes and evidence requirements necessary for
practice integration and coverage. The evidence should also be juxtaposed
against practical cost-benefit analyses persuasive to payers. As related to
clinical trials, design must serve multiple purposes beyond regulatory
approval. Trials should play a role in establishing clinical utility for payers,
informing clinical guidelines, customizing value-based evidence for different
stakeholder needs, e.g., payment structures, provider approaches and clinical
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guidelines. This arena of value recognition aligns most closely with the
standards of practice development theme of this dissertation.
• Infrastructure and information management. Health systems infrastructure and
information management are challenged by ill-equipped capacity for handling
the massive and complex information flows that characterize precision
medicine. The solutions are human- and financial-resource intensive requiring
coordination of institutional policies and processes for effective
communication across all services and specialty groups in the provider
continuum. Assuming electronic health records are in place, assuring that
individual genetic data and clinically actionable variants are captured, and that
all medical data, clinical support and outcomes information are standardized
across information platforms. Such a goal transcends precision medicine and
remains a goal of conventional practice. Similarly, methods of data input and
data interpretation must be simplified or customized for practical clinical use
by physicians. Moreover, adverse events should be captured and linked to
pharmacogenetic information on an individual and population-wide basis.
Policies should encourage proactive data sharing and set the groundwork for
learning health systems and the use of artificial intelligence.
• Ensuring access to care. The PMC (2017) study also notes that health care
systems processes, and procedures are optimized for traditional trial-and-error
and fee-for-service practices resulting in disincentives for the use of
personalized medicine products and services. In response to these needs, there
are numerous necessary measures such as development of incentives for
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payers to cover novel technologies with value-based evidence accumulation.
With respect to maintaining actionable information, policies that ensure the
updating of clinical guidelines and support tools are focused on providing the
best treatment strategies. On a broader basis, the prevailing lack of incentive
and compensatory schedules for providers and producers must be addressed
for services and diagnostic testing such as biomarker variant analyses. The
relative scarcity and marginalization of genetic analysis experts and
counselors in the current health care milieu must be changed and inclusion
into the precision medicine processes must be streamlined. Precision medicine
principles and practices must be included in alternative payment and delivery
models.
Such are the analyses and recommendations of the PMC as captured in Pritchard et al, 2017. As strong and thorough as they are, they are often framed in the passive voice throughout the article. This is not a semantic critique but merely an indication that defining and identifying parties responsible for leading the changes implicit in the recommendations are perhaps the missing component for the integration of precision medicine into health care practice, and suggestive of issues to be probed in the interviews for Study 2.
To put a finer point on the challenge, the PMC analysis does not directly address the organizational dynamics and inter-relationships of the stakeholders, particularly at the provider level. This is the essence of the title of this manuscript: “Organizational antecedents to the implementation of precision medicine: overcoming resistance to change.” PMC’s analysis and recommendations are well-researched and documented and
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thus operationally necessary. They are, however, organizationally insufficient. Only by
probing the conditions in place where precision medicine is operational and comparing
those conditions with the status of development at other providers can the organizational
foundations be established. Moreover, this manuscript’s further objectives in addressing the role of standard of practice development and business model reconciliation might provide a partial solution by identifying leadership roles and an actionable agenda for precision medicine. In order to further develop the context, it is necessary in the next section to demonstrate the inevitability and role of precision medicine in the evolution of the pharmaceutical industry.
Revisiting the Arguments
To refresh the reader, Study 1 was formulated to argue two points and establish the basis for a third:
• One, that precision medicine represents a paradigm shift in health care.
• Two, that resistance to precision medicine is essentially resistance to the paradigm
shift.
• Three, that there are determinable and manageable reasons for this resistance.
The first argument has been framed above and will be supported below. Similarly, the inventory below and in the Appendix of available and future precision therapeutics and companion diagnostics will clearly demonstrate that providers have the foundation for practice and a growing array of clinical practice options, thus supporting Argument 2.
Clinical resistance has also been demonstrated through discussion of the literature, particularly Pritchard et al, 2017, and the argument will further rest on precision medicine
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being a paradigm shift, thus setting the stage of setting up the balance of Argument Three
for treatment in Study 2.
Research Questions, Methodology and Data Sources for Study 1
Methodology
Based on the foregoing concepts and history of the evolution of precision
medicine, Study 1 frames five research questions:
Question 1: Is the practice of medicine undergoing a paradigm shift towards
precision medicine and what are the drivers?
Question 2: What is the status of precision medicine therapeutic offerings?
Question 3: What is the status of precision medicine diagnostic offerings?
Question 4: What are the economic and commercial realities of precision medicine?
Question 5: If conditions indicate that precision medicine is a paradigm shift, what are
the implications for organizational and professional practice?
To answer these questions, the research methodology of Study 1 has two
components: 1) historiography and, 2) quantitative analysis of product offerings and their clinical applications.
Methodological Component One is a historiography of two key elements. The first element was the foregoing analysis of the history of medicine and the life sciences within the framework of the Kuhnian paradigm shift model. Kuhn postulated his
Structure of Scientific Revolutions (1962) around physics. Kuhn and the scholarly
community have applied the paradigm shift model to the physical sciences extensively.
There has, however, been little exploration of medicine and the life sciences in the
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Kuhnian context owing to the fundamental differences between the physical and life sciences (Nickles, 2017).
This author, therefore, constructed a unique characterization of the structure of life science revolutions (Table 1) in order to demonstrate that precision medicine is a manifestation of major historic impact. The sources for the first element of history are primary readings of classical original and contemporary texts identified here:
Classical Texts Contemporary Texts
Selections from the Hippocratic corpus (c. 460 – Abu-Asab et al, Avicenna’s Medicine (2013) 420 BCE) Afshar et al, Andreas Vesalius and de Fabrica Aristotle, De Anima (c. 350 BCE) (2019)
Aelius Galen, Method of Medicine (c 175 CE) Barnes, The Complete Works of Aristotle (1984)
Avicenna, Al-Qanun-fi-al-Tibb (c 1010) Cambiaghi, Andreas Vesalius (2017)
Andreas Vesalius, De Humani Corporis Fabrica Casadevall et al, Revolutionary Science (2016) (1543) Flexner, The Flexner Report (1910) Karl Linnaeus, Systema Naturae, 1735) Antoine Lavoisier, Works on physiology (1777) Johnson, The Ghost Map (2006)
Charles Darwin, On the Origin of Species (1859) Judson, The Eighth Day of Creation (1979)
Gregor Mendel, “Versuche über Pflanzen- Nickles, Scientific Revolutions (2017) Hybriden” (1866) Polansky, Aristotle’s De Anima (2007) John Snow, Mode of Communication of Cholera (1855) Porter, The Cambridge History of Medicine (2006)
Louis Pasteur, On the extension of the germ theory Starr, The Social Transformation of American to the etiology of certain common diseases (1880) Medicine (2017)
Strohman, The Coming Kuhnian Revolution in Biology (1997)
Vegter, Towards Precision Medicine: A New Cosmology (2018)
Watson, The Double Helix (1968)
Zargaran et al, Avicenna (2012)
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The second historiographic element of Study 1 chronicles the development of
precision medicine within the larger context of organized medicine, medical practice, and
the evolution of the biopharmaceutical industry. This chronicle is based on a summary distillation of the surveyed and summarized literature (Table 3).
The function of these two elements of history is to establish the argument that precision medicine is itself part of a paradigm shift and that the first order challenge to the implementation of precision medicine is a function of resistance to any classical paradigm shift. In this case resistance takes the form of institutional inertia, practitioner reticence grounded in communities of medical practice, and cautious integration of the armamentarium of regulatory approved precision medicines and related diagnostics into normal medicine. This last point, however, is illustrated empirically.
Methodological Component Two: The second methodological component of
Study 1 is quantitative. It is comprised of original inventories and statistical groupings of the clinical applications of approved precision medicines and related diagnostics, and an additional inventory and statistical grouping of the same products currently in the global development pipeline (Appendices 2 through 4). The sources for this inventory and analysis are:
• US Food and Drug Administration website and clinical development data base
(publicly accessible as www.fda.gov; FDA, accessed during Autumn, 2019);
• PharmaProjects Data Base of Therapeutics (accessible through subscription
fee with Citeline at https://pharmaintelligence.informa.com/ ; accessed
through Autumn, 2019);
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• PharmaProjects Data Base of Companion Diagnostics (accessible through
subscription fee with Citeline at https://pharmaintelligence.informa.com/ ;
accessed through Autumn, 2019);
• Personalized Medicine Consortium compendium of approved precision
medicines (publicly accessible; see reference PMC, 2018);
• The 2020 to 2025 World Outlook for Precision Medicine (accessible only in
book form; see references cited Parker, 2019).
The function of the product inventories and statistical groupings of their clinical
applications are to establish a material and materiel basis for the readiness of the health
care community to be transformed by the availability of existing precision medicine
products available now and in the future through the global pipeline of products in
development. The function of the analysis of forecast global demand is to illustrate the
relative demand (but not readiness) among nations for the precision medicine approach to
disease prevention and intervention. Antecedent conditions for the implementation of
precision medicine, especially the resistance despite the comprehensive availability of
clinical tools begs questions as to why. These questions are the subject of Study 2.
Data Presentation and Analysis
Framing Argument One: The Structure of Paradigm Shifts
Kuhn’s Principles for Paradigm Shifts. Arguably, based on discussions in a wide variety of circles and disciplines, and the 96 million hits on a Google search, the term “paradigm shift” might have been among the first “viral” terms. By the simplest definition, a
Page 104 | 477 paradigm shift is a fundamental change in approach or underlying assumptions. It is this simple definition that allows the widest use of the term and has, as such, diluted its significance. In common parlance, the term is often applied whenever there is a change in the way of doing things, especially when driven by a technology or a popular movement.
The concept was initially published in 1962 by Thomas Kuhn, a philosopher of science, in The Structure of Scientific Revolutions, one of the highest cited academic books.
Kuhn’s intended use of the term, although somewhat ambiguously defined in his book, was certainly not the casual descriptor it has become. Indeed, Bird’s (2018) contribution to the Stanford Encyclopedia of Philosophy offers that:
Kuhn’s contribution to the philosophy of science marked not only a break with several key positivist doctrines, but also inaugurated a new style of philosophy of science that brought it closer to the history of science. His account of the development of science held that science enjoys periods of stable growth punctuated by revisionary revolutions (Bird, 2018).
This is hardly the stuff of casual reference. The significance of Kuhn’s work to this dissertation is that when a revolution or paradigm shift occurs in a fundamental tenet of knowledge, there is a dramatic new matrix for looking at the world, interpreting phenomena, analyzing cause and effect, and therefore answering questions or solving problems. Whenever the fundamental basis of understanding the world or a discipline is punctuated by a wholly new idea, it can take decades or even a century to alter scientific processes, cultural fabrics, or religious belief systems. Sometimes, professional, or religious persecution must also wane. This section of the dissertation endeavors to position precision medicine as a true paradigm shift in the history of medicine as a way of arguing that resistance to its adoption is rooted in issues far more fundamental than
Page 105 | 477 organizational or professional preferences. If the argument is successfully made, there are dimensions of resistance to change to precision medicine that must be addressed as antecedents to basic organizational dynamics. True paradigm shifts have been so rare – as characterized in the Introduction – that there is scant occasion to study their impact in change theory.
Kuhn’s characterization of the progress of science was itself a shift in thinking.
Prior to his work there had been little attention to an explanation of scientific change. The prevailing view of science had been that it develops by the accumulation of “new truths” or more precisely new insights or corrections of existing ideas. Progress could be the result of the work of a revolutionary scientist, but the standards associated with the scientific method itself democratized the opportunity to contribute to science. Implicit in
Kuhn, the evolution of a scientific idea does not progress uniformly. Rather, there are
“normal” and “revolutionary” periods. Revolutionary periods do not represent simple accelerated progress but have a qualitatively different spin on phenomena. Normal science generally is the most obvious and expected course of progress. It is often the most tangible because normal science is characteristically the basis for technological innovation. There is an underlying process that generally follows rules or patterns.
According to Kuhn (1962), scientific revolutions involve a revision to existing scientific belief or practice. When there is a revolution, the achievements of the prior period might or might not be preserved and when they are preserved it is often with a different understanding of the underlying phenomena. It is also possible that pre- revolutionary theories no longer hold-up once there is a fundamental change in thinking.
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This is sometimes referred to as “Kuhn-loss” or as John Casti frames it poetically,
Paradigms Lost (1989) and Paradigms Regained (2000).
Normal science, in Kuhn’s conception, succeeds when there is a strong
commitment to a body of beliefs, as well as shared values, an accepted inventory of
analytic standards (or instruments) and methods of testing and measurement. This milieu
is called a “disciplinary matrix” and is the foundation of normal science which progresses
and self-replicates through peer review and a structured education of new scientists.
Framing normal science this way is not a critique but rather a celebration of how
knowledge reliably accumulates. That said, normal science in Kuhn’s view neither tests
nor confirms disciplinary matrices. Generally, anomalous results do not necessarily nullify prevailing theories. Anomalies can be rationalized or explained away, but intellectual honesty is maintained through peer review. If an anomaly is persistently
recalcitrant, it can undermine the normal science processes. If wholly unresolved, an
anomaly can cause what Kuhn calls a “crisis.”
If a crisis is severe enough – e.g., the case of medicine in the 19th century when
the miasma or bad air theory of disease reached its descriptive limits and was challenged
by inconsistencies – thinkers may devise a revised disciplinary matrix that allows for the
elimination of the most severe anomalies and provides solutions for questions that the
prior matrix could not answer. That is the stuff of scientific revolution and constitutes a true paradigm shift.
Use and Abuse of “Paradigm Shifts” in Describing Medical Change
The objective here is to elevate the revolutionary origins of precision medicine.
Medicine is built on the process of rationalization posited by Max Weber (1946), namely:
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calculability, predictability, and control, but these factors were not always so and
emerged only after a series of shifts in medical thought that now culminates in precision
medicine. Whether or not the term “paradigm shift” is applied to precision medicine, its
emergence quantitatively and qualitatively elevates the stakes from other major and
minor changes in the practice and delivery of care. The historical positioning can be
demonstrated by using the above formulation as strict criteria for determining a paradigm
shift.
In the previous section, this study satisfied the four markers of paradigm shift
realization: frames of reference; investigational activities; contribution to the new body of
knowledge and approaches to theory formulation. Moreover, recall Table 1 (page 12)
in the Introduction which presented a historical breakdown of the author’s delineation of paradigm shifts in the life sciences and in medicine. Two conclusions were drawn: 1) paradigm shifts in medicine were trailing phenomena of paradigm shifts in life sciences;
2) the common thread through all medical paradigm shifts was the change in the understanding or re-characterization of the nature of disease including the genetic lineage.
A further argument for including precision medicine among the few paradigm
shifts that have occurred historically is to recognize that the goal is not solely to
individualize medicines or eliminate “off the rack” approaches to treatment. Berman
(2018) emphasizes other roles that precision medicine is playing that position it squarely
as a paradigm shift. Although Berman does not use the term, his characterization is
congruous with the principles of a paradigm shift. His arguments paraphrased are that
principally, disease develops in steps as a result of many causal factors and parallel
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processes that act over time. Observation of these steps or a disease pathway is now
technologically possible in such a way that precision medicine provides multiple disease
targets – a molecule in the body, usually a protein, that is intrinsically associated with a
particular disease process -- for intervention along the pathway. The recognition of
different pathways of disease development can lead subtyping of diseases according to
their biological pathways allowing treatments to be precisely targeted to subtypes of
diseases that were formerly indistinguishable from one another (Berman, 2018). The
notion of precision, therefore, can be redefined because diseases that have appeared
unrelated might share targetable pathways. Intervention opportunities are broadened, not
narrowed. This interpretation of precision medicine vis-à-vis the conception and classification of disease has similar elements to the movement of science towards the
Germ Theory of Disease.
Factors Influencing and Signaling a Paradigm Shift
Table 1 (page 12) in the Introduction represented the life science and medical paradigm shifts that the criteria posited herein allow, although the seeds of possibly two others are in the sowing. One of these, a shift from the “disease-care” paradigm that has characterized the health system built on allopathic medicine to a truly “health-care” paradigm (Heikkinen, 2000) arising from more holistic and patient-centric approaches to care, will be abetted by precision medicine. While such a shift flirts with the definitions of paradigm shift delineated above, it is revolutionary from a systems perspective, not necessarily from an underlying change in the fundamentals of medicine. The second shift visibly in the offing also relates to precision medicine and a theme of this study as related to standards of practice. Eitel et al (2000) argue that the emergence of algorithms in
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medical standards is an emerging paradigm shift. This was prescient given the attention
to artificial intelligence over the last two decades. They observe:
Medicine has evolved toward rationalization since the Enlightenment favoring quantitative measures. Now a paradigm shift toward control through formalization can be observed in health care whose structures and processes are subjected to increasing standardization. However, educational reforms and curricula do not yet adequately respond to this shift (Eitel et al, 2000). The remedy of Eitel et al (2000) echoes many of the principles of precision
medicine. They advocate an educational format dubbed “evidence-based
learning” consisting of structured decision making about implementation. The
purpose and thrust of that article is in the context of medical education, but it
foreshadowed some of the necessary conditions that should be established in
transforming medical practice to enable precision medicine.
Casual perusal of Google reveals hundreds of purported paradigm shifts in medicine such as the advent of anesthesia, sterile technique and antibiotics as revolutionizing surgery (they did, but the conception and purpose of surgery itself remained the same); the radiographic and magnetic imaging revolution in non-invasive diagnosis (major technological breakthroughs but are tools, not a new way of thinking); even the transformation of international health to global health to planetary health have been posited as revolutions (this transformation does represent a major change in thought processes but does not proceed from a foundational new way of knowing). To be sure, modern science produced the insights that led to the technologies that enabled progress, but all are part of the scientific medicine disciplinary matrix. That matrix has remained
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The Economics of a Paradigm Shift: Value Chains, Organizations, Business Models and Professional Dynamics
Misalignment of business models among precision medicine providers and producers.
The provider – producer – payer value chain or set of stakeholders is well characterized and accepted (Burns, 2002). Beyond contributing to the health of patients, there is significant variance in the mission, goals, and business models of the participating stakeholders. The health system, nevertheless, functions. Will the same variances hold true in precision medicine or are the participant’s business models in greater misalignment? Is the composition of the stakeholder landscape in precision medicine quantitatively or qualitatively different? Do the same concessions and accommodations for competing needs when services are delivered apply, or is there an additional layer of complexity confounding a ready translation to precision medicine? A case can be made that although essentially similar, the business model differences are more intense. Each of the stakeholders must reevaluate and devise an approach to their role in precision medicine. The challenge is that the actors are acting in parallel but with a set of individual circumstances that are in flux, i.e., business and revenue models as they relate to precision medicine are moving targets with needs for innovation.
Business models, and their related revenue models, are a function of management processes for translating products and service ideas into profitable innovations which sustainably generate value (Chesbrough & Rosenbloom, 2002). Specifically, business models illustrate the “. . . content, structure and governance of transaction designed so as
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to create value through the exploitation of business opportunities” (Amit & Zott, 2001).
Business model innovation often exists at simultaneous levels in the pharmaceutical
industry where product development generates incremental improvements for patient
care. In the case of precision medicine, the issue of business models is not merely a tool
for strategic analysis but must themselves be the focus of innovation (Eppinger &
Kamprath, 2011).
The substantial body of literature on business models provides several best-
practice approaches to innovation. These can be collectively summarized as:
• Organizational learning through trial and error in dynamic environments
where risk-taking is a necessity. In the aforesaid matter of business models
as moving targets, firms must necessarily experiment if there are criteria
for defining and measuring success.
• Institutionalizing a business model innovation process for exploration,
planning and implementation.
• Establishing an open innovation portal for both internal and external
sources of innovation and collaboration.
• Aligning new opportunities with existing capabilities so as to make best
use of internal traditions and new opportunities in the market (Floyd &
Lane 2000; Mitchell & Coles 2003; Nelson, 2008; Chesbrough, 2009;
Teece, 2010).
These criteria can be applied in turn to the three major stakeholders in precision medicine
(not including the patients): pharmaceutical, biotechnology and diagnostic companies; provider organizations; and, physicians. Of course, the framework can be extended
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further to include payers, such as CMS and private insurers, regulatory agencies, and
other ancillary service providers, but the purpose of this section is to highlight the business model misalignment as an obstacle.
How Precision Medicine Challenges Producers and Other Stakeholders
For producers such as pharmaceutical, biotechnology and diagnostic laboratories,
precision medicine’s impact is through pharmacogenomics which is the ability to test for
variations in gene sequences and how they affect expression using molecular diagnostics
which might promote potential treatment with highly targeted therapeutics. As intimated
previously, there are advantages for patients and other stakeholders, in particular, highly
targeted intervention, better and more predictable outcomes, identification of patients
who will respond to a given medicine, and reduction of adverse reactions to
pharmaceuticals. Surrounding these benefits are more ambiguous implications for
business models of the producers. Specifically, the precision medicine paradigm changes
in unprecedented ways the innovation and commercialization strategies across every
aspect of the research and development process.
Institutional Theory Applied Precision Medicine Adoption
This milieu of change invites a reconsideration of the framework of relationships among the stakeholders. Mrak et al (2017) advocate transaction cost economics (TCE) drawn from Institutional Theory as a means for identifying relationship patterns among the industry actors in precision medicine. They write:
Relationships among industry actors are expected to evolve depending on the manifestation of many contextual factors and
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their developments: investment activity, public interests, technology development, market structure, regulatory environment, demographic factors, personal preferences, natural factors, etc. . . . a descriptive model of an industry should include a broader scope of entities besides directly competing firms . . . market actors in a resource dependent environment sustain their activity by engaging in (bargaining) relationships with other entities with vested interests in the industry . . predictions of future industry and particular entities’ business model development would be a function of available resources, power relations and regulation. (Mrak et al 2017).
Consistent with these observations, Mrak et al (2017) distill three economic consequences of the precision medicine paradigm: 1) by its nature of segmenting patients along genetic or other factors, patient groups are smaller, not whole, or broad populations. The carefully choreographed nature of treatment processes is necessarily disrupted as are any economies of scale built into the systems. 2) On the industry and market level, technological innovations absorb large development costs and market development investment which lead to concentrated industries and market power. In precision medicine the tables are turned somewhat because technology diffusion dominates over technology creation through the biologically segmented market’s need for personalized care. Markets do not develop the same way they do under blockbuster pharmaceutical strategies and, therefore, the frameworks used to measure return on investment are undermined. 3) There are social costs associated with precision medicine creation and diffusion. Irrespective of the source of payer’s resources – public or private
– promotion of precision medicine dilutes resources of prevailing health services. In economic terms, the resulting disruption of power relations further confounds the reconciliation of rival business models. These are the economic factors underlying business model misalignment.
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Evidence for Argument One
The Crisis Precipitating the Paradigm Shift to Precision Medicine
Traditional care delivery models direct many physicians to prescribe therapies based on population-wide effects. Consequently, health systems globally deliver inefficient care that does not meet the needs of the patient population. Precision or individualized medicine is a new way of thinking about medicine through which physicians use diagnostic tests to identify specific biological markers, often genetic, to determine which medical strategies are optimum. The combination of this laboratory analysis together with a patient’s historical medical records, family history and genetics, circumstances, and expectations, enables physicians and patients to implement targeted treatment and prevention plans. Precision medicine can detect the onset of disease at its earliest stages, attenuate progression of disease, and do so in the milieu of meeting the health care triple aim: improving quality, accessibility, and affordability (Berwick,
2008).
In order to support the precision medicine thesis, data has accumulated that demonstrates in many instances that a pharmaceutical has limited or no effect on half or more of the patients for whom it is prescribed as illustrated in Table 7.
Precision medicine represents a true paradigm shift in the history of medicine with the precipitating crisis being the imprecision with which medicines are selected and prescribed. Resources are limited throughout the world and the experimental attempts at finding the right pharmaceutical at the right time is an enormous inefficiency as well as a basis for unnecessary suffering for the patients. The underlying science of precision
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Table 7: Response rates of patients to a major drug for a selected group of therapeutics areas
Therapeutic area Efficacy Rate (%) Alzheimer’s 30 Analgesics (Cox-2 inhibitors) 80 Asthma 60 Cardiac Arrythmias 60 Depression (SSRIs) 62 Diabetes 57 H epatitis C Virus 47 Incontinence 40 Migraine (acute) 52 Migraine (prophylaxis) 50 Oncology 25 Osteoporosis 48 Rheumatoid arthritis 50 Schizophrenia 60 Source: Spear, Heath-Chiozzi, Huff, J. (2001) medicine in historical terms is a radical departure from the disease modeling and staging that prevailed throughout the 20th century. Its implementation is also a cataclysmic shift away from the population-based statistical determinism that has driven medical decision making for generations.
Medical practice can now move away from one-size-fits-all, trial-and-error experimentation towards a targeted approach based on patients’ molecular information.
This approach better informs therapeutic strategies. Such a transformation, however, demands a global collaborative effort to absorb the pace of scientific and technological progress. Of course, progress in the direction of precision medicine is subject to additional constraints, including regulatory regimes, reimbursement constraints and the always elusive development of clinical standards of practice.
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Cancer Targeting as a Further Example. Precision medicine has already been applied in
cancer diagnosis and treatment, specifically in the understanding of oncogenes
(mutations prone to cancer) and oncogenesis (origination and proliferation of cancer).
This process informs the discovery of potential targets for therapeutics development by
Table 8: Precision Medicine’s Status in Cancer Care. Percentage of patients whose tumors are driven by certain genetic mutations that could be targets for specific therapeutics, by types of cancer. Melanoma 73%
Thyroid 56%
Colorectal 51%
Endometrial 43%
Lung 41%
Pancreatic 41%
Breast 32%
Other gynecological 31%
Genitourinary 29%
Other gastrointestinal 25%
Ovarian 21%
Head and Neck 21%
Source: Winslow, R. Major shift in war on cancer. Wall Street Journal. June 5, 2011. Accessed June 3, 2019 at http://www.wsj.com/articles/SB10001424052702304 432304576367802580935000.
blocking the expression of oncogenes by inactivating them or their pathways. This
concept, which is already clinically applied, is the basis for treatment of chronic myeloid
leukemia (CML). Allogeneic (donor-sourced) bone-marrow transplants had long been the standard of practice particularly for younger patients. The discoveries of molecular
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predispositions that generate a variety of diseases enables the development of more
specific medications aimed at new molecular targets. The impact of precision medicine
on cancer care is illustrated in Table 8.
Status and Light Use of Genetic Tests. Genetic testing is one of the gateway
technologies to precision medicine. Recent data is unavailable but according to Concept
Genetics (conceptgenetics.com) as of September 2016, there were 65,839 genetic testing
products on the market with 5,500 becoming available in the 18 months leading up to that
point. The growth in the availability and use of these tests is especially visible in
oncology as established in Jorgensen (2015) which describes the emergence and growth
of Companion Diagnostics (CDx). These assays, according to the US FDA guidance
document of August 2014 are defined as laboratory diagnostic devices that provide
information that is essential for the safe and effective use of a corresponding therapeutic product. The best-known example of a CDx is the predictive assay for overexpression of
HER2 (HercepTest®) developed in conjunction with trastuzumab (Herceptin®) for the treatment of advanced breast cancer in 1998. The co-development strategy for these companion products established the model for future development (Bazell, 1998).
The companion approach relies on a thorough understanding of the biology of the disease vis-à-vis the mechanism of action of the pharmaceutical. This pairing of insights has been elusive for most pathologies with the exception being oncology because of the level of molecular understanding of the patient’s and the tumor’s sequence. There is a compelling historical contrast when looking at the work of Spear et al in 2001 in assessing the efficacy of cancer chemotherapy, the standard of practice for most cancers at the time, found that the efficacy rate was 1 in 4. (Spear, 2001). Nearly 20 years later,
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the picture is improved. Jorgensen (2015) demonstrates that pharmaceuticals released
since 2001 with a CDx have a higher response rate than the pharmaceuticals previously
used for the same conditions. Specifically, for the companion products studied there was
a response rate of 80.2% to 34.0%. Those products not paired with a diagnostic assay had
response rates ranging from 6.8 % to 45%. These comparisons may be equivocal and
similar results have not been obtained outside of oncology. Jorgensen (2015) concludes,
“no doubt, more widespread use of pharmacogenomic biomarkers would lead to a more
rational and cost-effective pharmacotherapy to the benefit of both the individual patients
and the health care system as a whole. However, apart from anticancer drugs, the pharma
and biotech companies do not appear to have prioritized pharmacogenomic biomarkers.”
These limitations are widely understood and acknowledged within the physician community which may be a factor in the slow pace of precision medicine adoption. This is a factor to be studied in Study 2.
Demonstration of Argument One
Study 1 can now summarize the formulation Argument 1. To review, the five main arguments of this dissertation are:
• One, that precision medicine represents a paradigm shift in health care (Study 1).
• Two, that resistance to precision medicine is essentially resistance to the paradigm
shift to molecular medicine that had its roots in the mid-20th century (Study 1).
• Three, clinical resistance to precision medicine exists and that there are
determinable and manageable reasons for this resistance (Studies 1 and 2).
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• Four, that the managerial strategies in place at leading institutions are definable
and reproduceable in other clinical environments (Study 2).
• Five, observations concerning resistance to precision medicine and their
management have implications for theories of organizational change (Study 2).
QED: Precision Medicine is a Kuhnian Paradigm Shift
Is the exploration of precision medicine as a paradigm shift an academic exercise or does it have relevance for implementation into practice? The similarity in the circumstances of the aftermath of a paradigm shift makes the question relevant. In 1543, when Copernicus posited the heliocentric model of the universe in order to explain the pesky meanderings of planets within their orbits, the geocentric pronouncements of
Ptolemy collapsed and along with them the poetic nature of science, philosophical understanding and justification, non-empirical validation, and authority. The intellectual effect rippled through every discipline, albeit some more remote in time than others.
Basically, the entire intellectual infrastructure of science changed and new languages, e.g., the calculus, needed to be invented.
As described in the Introduction, major new insights or technologies found their way into standards of practice either immediately or after accumulation of population- wide evidence. The establishment of standards of practice, however, occurred through relatively focused communities of specialists – communities of practice – and sub- specialists and migrated to general practice where appropriate. The physician-centric model of health care enabled the establishment of such standards, and the standards development process was later validated by the Institute of Medicine (2011).
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As the stakeholder landscape of health care has changed wherein patient
advocates, producers and payers have accumulated influence over the practice of
medicine, the criteria and process for standardization of practice has become slower and
more complex. There is no precedent in medical history for an approach to care as
complex and stakeholder intensive as precision medicine. The science that enables
precision medicine requires participation by a wide array of specialists who generally are
allied though their own specialty societies.
On the practitioner level, for a standard of practice to emerge, there must be
convergence of the specialty societies. Each society, however, may be affected by the
underlying science in a different way and over a different time span, and may not have
the same level of investment in possible clinical outcomes. Similarly, the non-physician providers, i.e., the hospitals and systems as institutions, have a differing set of concerns
in meeting the expectations of patients, donors, payers, and regulators.
The product and service opportunities for producers also emerge at a different pace and the creation of new business opportunities likely requires participation of an array of partnerships that is certainly precedented in the biotechnology revolution but not necessarily to the extent that precision medicine demands. New products are also developed in an environment of regulatory oversight that is making an all-out effort to accommodate to the science and update its methodologies, but regulators are beholden to
stakeholder networks despite their legally mandated independence.
Payers must provide subscribers with contracted benefits but at the same time
must protect the financial integrity of their subscriber base. As precision medicine
penetrates more arenas of care, payers have a conflicting advocacy responsibility to cover
Page 121 | 477 those costs where benefits are observable and quantifiable. Finally, patients and advocacy groups must build consensus among themselves and ultimately with other stakeholders whose needs are not necessarily aligned. Paradigm shifts wreak havoc where at once they demand change but promote resistance until a new disciplinary matrix emerges. Precision medicine is not business as usual for providers, producers, or payers. Mediation into a comprehensive milieu of practice requires the examination described in Pritchard et al
(2017), but a deeper explanation of organizational and practice dynamics as advocated in
Study 2 is necessary because of the impact that precision medicine has as a paradigm shift.
Does the Literature Support the Conclusion that Precision Medicine is a Paradigm Shift?
Biologists and philosophers of science periodically raise the question of whether the strictest definition of Kuhn’s paradigm shift concept can be applied to biology and, therefore, medicine. It is an unresolved question, although there is a recent history of discourse largely inspired by the molecular shift. That said, the literature has not made a case or reached a conclusion in denial or support of this dissertation’s Argument One.
It is worth reviewing several articles beginning with Halloran (1984) who recounts the history of the publication of the Watson & Crick (1953) paper that goes beyond the scientific revolution that it triggered. Halloran makes a case that the impact of the publication when coupled with the personalities of the authors created a new ethos of biology. Writing in the early days of the rise of the biotechnology industry, Halloran writes that “there is today an adventuresome, entrepreneurial, slightly irreverent spirit associated with the field of molecular biology and genetic engineering, a spirit that on its
Page 122 | 477 face strikes me as a recognizable offspring of the Watson-Crick ethos” (Halloran, 1984).
He also argued that Watson & Crick (1953) “have influenced not only the ideational content of biology, but the manner in which ideas are pursued, the spirit in which science is done” (Halloran, 1984). Does this support this study’s positioning of the
Molecular/Genetic Paradigm prominently in modern times? Perhaps, but for reasons that
Kuhn would not likely have recognized.
Strohman (1997) offers an additional critical assessment of Watson & Crick
(1953). He grudgingly acknowledges that their work is the foundation of a scientific revolution but, like Halloran, decries the direction in which the work has taken biology. It is a paradigm shift, he believes, that reinforced genetic determinism. He writes:
. . .there is the excitement of recognizing in contemporary biology many of the attributes of a Kuhnian revolution. These attributes have been summarized recently by the biologist Adam Wilkins who, while giving Kuhn credit for jogging the biological imagination and for awakening (temporarily) its mostly dormant theoretical aspect, delivers the opinion that, in biology, Kuhnian revolutions have never really happened. I think he may be right for the three cases he has examined: Mendel, Darwin, and Watson-Crick. But I think he misses the point that the Watson-Crick era, which began as a narrowly defined and proper theory and paradigm of the gene, has mistakenly evolved into a theory and a paradigm of life: That is, into a revived and thoroughly molecular form of genetic determinism. The paradigm of the gene stands as a model that has presided over the development of an extremely successful molecular biology that continues to reveal the enormous complexity of living things. As a paradigm of life- genetic determinism-it is an illegitimate offspring of the former, showing all the real signs of a Kuhnian revolution. In promising to penetrate and reveal the secrets of life, it has extended itself to a level of complexity where, as a paradigm, it has little power and must eventually fail. The failure is located in the mistaken idea that complex behavior may be traced solely to genetic agents and their surrogate proteins without recourse to the properties originating from the complex and nonlinear interactions of these agents (Strohman, 1997).
Although Strohman provides an engaging and interesting article, his assessment bears indirect relevance to this dissertation’s arguments, but his assertions are suggestive of a
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change of thought patterns in the scientific community, the issue of genetic reductionism
aside which is an ethical position, not epistemological. The assertions, otherwise, do
support this thesis.
Portin (2015) supports the position herein that the Molecular/Genetics Paradigm
is real and describes the history in such a way that support the Mendelian Paradigm shift,
as well. He writes that the
important extension of the Mendelian paradigm of genetics was the invention of the DNA theory of inheritance, which culminated first in the discovery in 1944 of the fact that in a chemical sense genes are stretches of DNA, and second in the discovery of the molecular structure of DNA in 1953. This was followed by the rapid advancement of molecular genetics, including the cracking of the genetic code and gene technology. With the DNA theory of inheritance, our conception of genes was now shifted from the cytological to the molecular level. . . During recent decades, the science of genetics has witnessed many new discoveries that seem to be genuine anomalies in the Kuhnian sense, and thus demand a paradigm shift. These discoveries include the existence of adaptive mutations and transgenerational epigenetic inheritance, and also many findings that have led to a complete reevaluation of the very concept of the gene. This reevaluation has meant a return to an open and abstract concept of the gene – a way of thinking that prevailed in the early years of the development of the initial concept of the gene. The concept of the gene is central in the emerging new paradigm, and our present impression of this concept appears to be reminiscent of a way of thinking characteristic to Systems Biology. Likewise, the entire emerging new paradigm of genetics appears to be an integral part of the proposed new paradigm of biology, the paradigm of Systems Biology (Portin, 2015).
This dissertation has not discussed Systems Biology and although not synonymous with
Precision Medicine it is integral to it as Portin argues.
There is some indirect support of this dissertation’s argument by Politi (2018) who in a philosophy paper seeks to develop the concept of scientific specialization which
Kuhn began to develop in his later writings. One of the theses of this dissertation is that precision medicine has emerged through a convergence of science and technology as
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practiced by communities of scientists and clinicians. If the notion of specialists is
liberally applied to these communities, Politi explains how precision medicine has risen
to the category of a paradigm shift. He writes,
It has been shown how the creation of new specialties fits Kuhn’s model of scientific revolutions. An account of specialty-incommensurability, that takes into consideration both its semantic and methodological aspects, has been outlined. These claims on specialization have been integrated and elucidated through the example of the discovery of the DNA structure, and of its relation to the creation and establishment of molecular biology. As Kuhn says, it is a simple matter of fact that the progress of science is linked to a proliferation of specialties (Politi, 2018).
Finally, Vegter (2018) confronts head-on the notion that precision medicine is a new biomedical cosmology, i.e., the strongest possible way of characterizing a paradigm shift. By exploring how precision medicine involves a transformation along three axes,
Vegter highlights key criteria for declaring precision medicine as a paradigm shift. These are:
the axis of biomedical knowledge, of biomedical power and of the patient as a self. Patients are encouraged to become the managers of their own health status, while the medical domain is reframed as a data-sharing community, characterized by changing power relationships between providers and patients, producers, and consumers (Vegter, 2018).
With that shared, Vegter is critical and cautious about the implications of precision medicine to the integrity of the individual and their ownership of their own data. The point, however, is that he builds his case on precision medicine as a paradigm shift when viewed in combination with changes in social dimensions of medicine, such as the rise of the patient-centric care model.
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Framing Argument Two: Status and Readiness of Precision Medicine
In order to frame the second argument, the next section of this study couples with the pharmaceutical history previously described and highlights the preference, but migration from, blockbuster products. As highlighted previously, one-size-fits all medicines are not efficacious for most patients for whom they are prescribed. Moreover, attempted development of blockbusters is low-yield and extremely high-cost.
Pharmacogenomics offers developers the potential of engineering pharmaceutical candidates with more specificity, less adverse incidents during clinical trials, and better justification for prescription for suitable patients. In 2005, the US FDA issued guidance for producers for the linkage of biomarkers to therapeutics with the expectation that over time development will be optimized and the utility of medicines would increase.
The pharmacogenomic story begins with oncology. While this dissertation has documented oncology’s current dominance of precision medicine, the applicability to other disease states has been demonstrated and is under development. In oncology, the stakes are high, and the consequences of therapeutic complications or failure are profound, thus the attraction. Despite these benefits, however, genomic-driven medicinal development overall is still in its infancy and cost savings are yet to be realized. In fact, precision medicines represent costly intervention at the current time. The business model implications from the producers’ vantage point include (adopted from Ferrara, 2007):
• For a time, significant price distortion of products for providers
and payers;
• Greater reliance on the availability and integrity of diagnostic
testing, which in the current environment is inadequately compensated
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given its role in interventional strategy selection and the overall cost of
health care; precision medicine dramatically highlights the need for
diagnostic technologies and services thus further distorting the prevailing
provider model;
• Precision medicine will accelerate the movement towards value-
based care as opposed to the prevailing fee for service business model.
Conceptually, precision medicine could force a reconfiguration of the
respective roles of medicines vis-à-vis the diagnostics. Pharmaceutical choices based on specific diagnostics may actually limit prescriptions initially, but over time, translate to total market share for a given therapeutic, albeit for a smaller segment of the overall market.
• Linking a diagnostic to a therapeutic – a companion – can have clinical and commercial benefits, but it also changes the development risk profile for the diagnostic company.
• Precision medicine will further accelerate the need for collaboration and alliances among producers, among providers, and between producers and providers (sometimes in selecting and modifying a therapy for individual patients), between producers and payers, and between providers and payers. The business models and commercial needs of these stakeholders can be aligned, but not without development of common purposes, definitions of desirable outcomes, means of measuring those outcomes and assignment of appropriate compensation for the risk and results (adopted from Ferrara, 2007).
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Evidence Supporting Argument Two
Over the last decade, the biopharmaceutical industry has begun to provide
precision medicines that target the unique characteristics of a patient and their disease.
This dissertation describes (Appendix B) over 150 approved precision medicines
approved since 2010, or approximately 15 per year, representing one-third or more of the
approved new pharmaceuticals during that period (Personalized Medicine Coalition,
2018).
The number of precision medicines and associated companion diagnostics in the
pipeline of US Food and Drug Administration (2019) approval process exceeds 200
(Appendices 3 and 4), suggesting that over the next 10 to 15 years, more than half of
pharmaceutical productivity will be precision medicines. Thus, although a subset of each
of the outputs of synthetic and biological pharmaceuticals, it can rightly be claimed that
the industry and medical practice have entered the aforesaid “Precision Period.”
According to Tufts Center for Drug Development, 42 percent of all drugs in development and 73 percent of oncology compounds are precision medicines.
Biopharmaceutical companies nearly doubled their R&D investment in personalized medicines over the past five years and expect to increase their investment by an additional 33 percent in the next five years. Biopharmaceutical researchers also predict a
69 percent increase in the number of personalized medicines in development over the next five years (Tufts Center for the Study of Drug Development, 2015). This can be
interpreted positively and negatively. The positive interpretations are that the inventory of
tools will grow; negatively, there will be a growing dependence on precision medicine
whether or not organized medicine is ready.
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Regulators and Regulation: Drivers and Impediments to Adoption. Regulation is often associated with obstruction but in the matter of the US FDA’s role in proactively developing an appropriate framework for the proliferation of precision medicines the
Administration has been a positive force. By way of example, nearly one-quarter of the medicines approved by the FDA from 2014 – 2016 were personalized medicines and the
trend continues. As a way or reaching consensus with the providers and producers, the
FDA regularly issues guidance documents. The FDA’s action was encouraged by the 21st
Century Cures Act of 2016 which promotes “real-world evidence,” patient centricity and a focus on molecular pathways in trial design. Regulation of personalized medicine, however, is still evolving and the approval process for diagnostics remains in flux.
Moreover, the FDA is reviewing its practices for laboratory-developed tests (LDTs) and next generation sequencing (NGS) That said, well-designed procedures are in place for co-development of medicines with companion diagnostics.
The FDA’s actions on LDTs are relevant for personalized medicine because in most cases these are used to make clinical decisions. Historically, diagnostic tests are subject to two regulatory pathways: diagnostic kits and LDTs. The kits provide users with a turn-key system for laboratory analysis but are regulated as medical devices. At the current time, only a small portion of LDTs are FDA-approved. Pregeli et al. (2018) also make the case for more rapid approval of precision medicines over “conventional” medicines.
According to the Personalized Medicine Coalition (2013), “clinical laboratories that perform LDTs are subject to the Clinical Laboratory Improvement Amendment
(CLIA) rules administered and implemented by the Centers for Medicare and Medicaid
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Services (CMS). Clinical laboratories can obtain CLIA certification directly from CMS,
typically through state agencies that survey labs for compliance with CLIA
requirements.” Traditionally the FDA has historically claimed jurisdiction on LDTs but
allows itself discretion in selecting one to review. The overall framework remains
ambiguous and there have been discussion documents and forums since 2014, but a
definitive process is still emerging. The FDA’s concerns about LDTs is articulated on its website as follows:
The FDA has identified problems with several high-risk LDTs including claims that are not adequately supported with evidence; lack of appropriate controls yielding erroneous results; and falsification of data. The FDA is concerned that people could initiate unnecessary treatment or delay or forego treatment altogether for a health condition, which could result in illness or death. The FDA is aware of faulty LDTs that could have led to: patients being over- or undertreated for heart disease; cancer patients being exposed to inappropriate therapies or not getting effective therapies; incorrect diagnosis of autism; unnecessary antibiotic treatments; and exposure to unnecessary, harmful treatments for certain diseases such as Lyme disease (FDA, 2019a).
The FDA is also studying the regulation of next generation sequencing (NGS) technologies. PMC (2017) notes that “while current regulatory concepts are applicable for the regulation of conventional diagnostics that measure a limited number of endpoints associated with a disease or condition, diagnostic tests that use NGS technology can examine millions of DNA variants at a time, and therefore require a more flexible oversight approach.” This represents a scientific and pragmatic challenge to be resolved but the agency has worked proactively with developers to formulate criteria as the science advances.
According to the FDA, “a companion diagnostic is an in vitro diagnostic or an imaging tool that provides information that is essential for the safe and effective use of a
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corresponding therapeutic product” (US FDA, 2019a). In 2014, FDA released its final In
Vitro Companion Diagnostic Devices Guidance, which helped clarify its method for
conducting simultaneous reviews of a drug and its companion diagnostic (USFDA,
2014). At issue was the sequence in which a companion product could be used in testing.
Conditions under which a targeted drug might be approved ahead of a corresponding
diagnostic test include the use of biomarker test prior to prescribing a given medicine. As
a guide and a means of encouraging development, the FDA publishes a table of valid
genomic biomarkers that it considers valid in guiding the clinical use of approved drugs
(USFDA, 2019b). The FDA, therefore, is balancing its mandate to protect the public with an agenda of advancing the public good through technology. This approach supports development from a producer point of view and is another indicator of response to a paradigm shift.
Profile of Approved Precision Medicines
Current approved pharmaceuticals with accompanying biomarkers appear in
Appendix B. The Appendix lists 120 pharmaceuticals whose use can be determined by testing against a listed biomarker. The compilation demonstrates that precision medicines have already been developed across a wide range of therapeutic indications. Table 9 is an original summary of available precision medicine by category of medical specialty. An important conclusion to be drawn from Table 9 is that precision medicine’s utility is not restricted to oncology, as is commonly assumed. There are already pharmaceutical products available across the spectrum of disease categories and disease states. The data in Appendix B has been abbreviated to provide essential information on the identity of
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Table 9: Summary of Approved Precision Medicines by medical specialty. See Appendix B for details
Clinical Category Number of approved pharmaceuticals Adjuvant Therapy 4 Analgesia and Anesthesiology 4 Cardiovascular 11 Endocrinology 4 Gastroenterology 5 Hematology 2 Immunology 1 Infectious Disease 17 Metabolic 1 Neurology 9 Oncology 32 Platinum Therapies 15 Psychiatry 16 Source: Personalized medicines were identified from the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling, accessed June 18, 2019 at https://www.fda.gov/drugs/science-research-drugs/table-pharmacogenomic- biomarkers-drug-labeling
the product, clinical indication and development status. The data bases and accessed
websites provided within the Table legends offer considerably more information.
Profile of Companion Diagnostics
Simply defined, a companion diagnostic (CDx) is a diagnostic test used as a companion to a therapeutic drug to determine its applicability to a specific person. CDx is
a resource central to most approaches to precision medicine because these tests determine
suitability for a therapeutic strategy or assist in monitoring response to the prescribed
medicine. Generally speaking, diagnostics are not reimbursed commensurate with their
clinical utility and the pricing and reimbursement of CDx remains an open question at
present.
Appendix C presents a compendium of 169 CDx in the development pipeline
derived from an original search of the Pharmaproducts/Citeline proprietary data base and
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the publicly available US FDA website. Of note, typically, the entity developing the test is not the same company that produces the related pharmaceutical. There is a historical
reason for that. Until the late 1980s, most of the pharmaceutical companies had
diagnostic divisions that either manufactured tests or provided diagnostic laboratory
services, or both. Wall Street analysts, at that time, signaled that given the gross margins
of pharmaceuticals, that companies should divest all non-pharmaceutical assets in order
to enjoy the most robust P/E multiples. By the 1990s, the industry had divested virtually
all diagnostic capability. In the era of precision medicine where diagnostic capability is
once again desirable, the pharmaceutical companies are generally not equipped to
Table 10: Breakdown of companion diagnostics in development by disease targets. Category Number of tests in development
Oncology 129
Infectious disease 11
Central nervous system 7
Immunology 1
Hepatic 3
Cardiology 4
Inflammation 3
Gynecology 2
Pulmonary 3
Gastroenterology 3
Ophthalmic 1
Hematology 1
Source: Companion diagnostics were identified from the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling, accessed June 18, 2019 at https://www.fda.gov/drugs/science-research-drugs/table-pharmacogenomic- biomarkers-drug-labeling and Pharmaprojects data retrieval, November 2018.
Page 133 | 477 develop diagnostics. They must either partner with a university, a diagnostic producer or laboratory for this purpose, or independent diagnostics companies actively developing diagnostics for precision pharmaceuticals on the market or in the development pipeline.
Like Appendix B, Appendix C demonstrates that although there is a bias towards cancer-related diagnostics, the diagnostics under development serve a broad range of clinical needs as indicated in Table 10. The data in Appendix C has been abbreviated to provide essential information on the identity of the product, clinical indication and development status. The data bases and accessed websites provided considerably more information.
Profile of the Precision Medicine Global Development Pipelines
Characterizing the development pipeline for precision medicines and companion diagnostics. This section poses and answers a research question exploring producer readiness and technology foundational assessment for precision medicine through an analysis of how precision medicine is technologically poised to be incorporated into patient care. The method was based on an inventory and statistical analysis of greater than 150 pharmaceuticals, many with companion diagnostics, either approved for use in care or in clinical trials and is an original compilation in the way it is presented. This data has been procured using archival data purchased from Pharmaprojects (a commercial organization tracking pharmaceutical related products in development), from the Food and Drug Administration’s on-line data sources, and from inventories compiled by the
Personalized Medicine Coalition (2019). This Section is a compilation of precision medicines on the market as approved by the FDA where a biomarker is identified that can direct the optimal use of the pharmaceutical or the current product pipeline of
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pharmaceuticals with companion diagnostics used to determine optimal or appropriate
use. The purpose of this section is to establish that the community of producers is actively
developing and marketing precision medicine products for patient care by providers.
To support further the findings that precision medicine is in an ever-increasing
state of readiness to be integrated into clinical care, Appendix D identifies 99 precision
pharmaceuticals in development suggesting that the approvals of new pharmaceuticals
over the next decade will have strong representation by precision medicines. The data is
derived from an original search of the Pharmaprojects/Citeline proprietary data base and
the publicly available US FDA website. Nearly all the products in the pipeline have multiple indications in a disease category and run the range of preclinical to Phase III
Table 11: Breakdown of precision medicines in development by disease targets
Category Number of meds in development
Oncology 76
Psychiatric/CNS 1
Infectious disease/immunology 10
Gastroenterology 4
Cardiology 1
Hematology 1
Metabolic 2
Dermatology 2
Ophthalmology 2
Source: Precision medicines in development were identified from the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling, accessed June 18, 2019 at https://www.fda.gov/drugs/science-research-drugs/table-pharmacogenomic-biomarkers- drug-labeling and Pharmaprojects data retrieval, November 2018.
Page 135 | 477 depending on the indication. Many of the indications are, however, niche or fall into the category of rare diseases. Most will also depend on the availability of a companion diagnostic. The data supports the position that precision medicine from a product point of view is sufficient to support adoption of the paradigm more widely than is currently the case. Table 11 identifies the number of products in development by disease category. The data in Appendix D has been abbreviated to provide essential information on the identity of the product, clinical indication and development status. The data bases and accessed websites identified in the Table legends provided considerably more information.
Economic Considerations in the Adoption of Precision Medicine
Health economists have been turning attention to the implications of precision medicine across a spectrum of economic issues. The National Bureau of Economic Research held a special convocation in September 2017 that explored the progress of personalized medicine. The convocation resulted in the publication of a comprehensive volume (Berndt, et al, 2019) of papers that represented the interrelationships of the milestones and issues as illustrated in Figure 13. This dissertation extracts observations from four of the papers for their value in informing issues that should be explored when conducting the interviews described in Study 2.
The Economic Value and Pricing of Personalized Medicine. Does the value of precision medicine rise uniquely from a single part of the process as opposed to health care generally? Arguably the value and optimal pricing of precision medicine rests in the value derived from the information produced by the use and results of the companion diagnostics.
The diagnostics either provides the green light to treatment and ideally a better outcome which can drive compensation of the provider, or the diagnostic signals a negative in which
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case the procedure does not proceed and there is no reimbursement, including the
diagnostic. The enterprise of precision medicine offers treatment-specific learning
innovations that serve both individual circumstances and the accumulated body of
Physician choice of precision medicine Insurance coverage therapy of Precision Targeted drug Medicine development by pharmaceutical Value of companies precision medicine
NIH investment in Competition and genomics and related pricing of diagnosis Cost effectiveness of Precision medicine fields and treatment Precision Medicine and health inequity
Figure 13: Progress of precision medicine and the interrelationship of milestones and issues. Source: Berndt, Goldman & Rowe, 2017.
knowledge. That knowledge ultimately promotes the quest to better match treatments to
patients and in so doing prevents inefficient over- and under-consumption by non-
responders and responders. Precision medicine converts treatments from being “experience goods” to “search goods”, which helps explain their emergence in cancer care where
learning through experience is the costliest as it can involve inefficient mortality and
complex morbidity, especially as the number of emerging alternative treatments grows.
A goal for the reimbursement for companion diagnostics – and perhaps the most
viable way for reaching appropriate pricing parity for diagnostics – is essentially a pay for
performance model that seeks to undertake treatment spending only on responders. It is,
therefore, intricately linked to standard pay for performance schemes that use treatment
experience as the mechanism by which treatment performance or quality is assessed.
Standard pay for performance schemes seek to compensate sellers only if the product meets
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expectations. For medical products this amounts to sellers providing goods free of charge to
providers and patients which is not a sustainable approach to a viable business or on-going
research and development. A task for precision medicine to overcome in order to evolve a
reasonable payment model is better insight into how the pricing of goods – experience goods based on outcomes – compares to simply paying for the companion diagnostic gate keepers to therapeutic products (Philipson, 2019). These issues will be framed for response during the interviews for Study 2.
The Value of Pharmacogenomic Information. For the precision medicine paradigm
to be implemented in a practical way, pharmacogenomics must be integrated into the overall
process. Despite the scientific obviousness and support of many physicians, funding
agencies and policy makers, pharmacogenomic testing has yet to be widely and routinely
adopted by health care systems, whether they be academic health centers or community
scale hospitals. Essentially, the obstacle is a lack of reimbursement by payers and little confidence that an array of multi-dimensional tests will yield improved health care outcomes on a population-wide basis at acceptable costs over a foreseeable time frame.
Graves, et al (2019) attempted to bridge key research gaps by developing a
methodological framework for assessing the long-term value of pharmacogenomic testing
strategies. In order to do so, their approach sought to overcome limitations in these types of
assessments by “broadening both the scope and time horizon for pharmacogenomic testing
to affect patient costs and health outcomes.” Their coupling of real-world evidence on pharmacogenomic implementation allowed them to identify scenarios where preemptive testing and single-gene testing are each cost effective. Their analytic approach differentiated when and in what circumstances pharmacogenomic testing strategies could be optimized
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and scored for comparative purposes to drive overall cost effectiveness. The Study 2
interviews will probe questions related to establishing these conditions.
Cost Sharing in Insurance Coverage for Precision Medicine. Pauly (2019) notes that there is considerable variation across clinical conditions and types of insurance coverage –
both the gross prices paid for genetic tests and genetic counseling, and for the prices of
treatments whose selection depends on test results. Prices of common genetic tests, he
observes, have been dropping as technology advances to as little as $200 to $500 for
common tests targeted at common parts of the genome but rise substantially when in search of variants and modifications. Reimbursement willingness and approaches differ among private insurers, but generally there is coverage that ranges from modest to nearly full cost.
Private insurers typically cover genetic testing under the same cost sharing provisions that apply to other testing.
People insured under Medicare have a different set of rules. Pauly (2019) further observes that Medicare cannot negotiate prices for Part D drugs for which there are no therapeutic equivalents, can only set prices for Part B drugs, and is required to cover all classes of clinically appropriate FDA-approved drugs. With respect to coverage of genetic testing, Medicare carriers have discretion but some variation in coverage exists.
Pauly’s (2019) review of coverage for genetic testing indicated a trend towards more general acceptance of clinical utility and, therefore, qualifying for insurance coverage.
Experimental tests continue to face reluctance and are faced with high bars for the evidence needed to justify routine coverage. He makes an interesting observation in this regard,
“though in most cases the coverage usually follows rather than facilitates clinical practice.”
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This is a matter for exploration in the Study 2 interviews. Another of Pauly’s (2019) observations also will be explored in the Study 2 interviews:
Genetic testing to determine the effectiveness of treatment is still relatively new, though growing rapidly. There does seem to be a common cycle in which three trends compete: evidence for and use of genetic testing increase over time, insurance coverage (though present) initially imposes higher cost sharing, then test prices fall and coverage improves and out of pocket costs falls (Pauly 2019).
The significance here is that the providers – institutions and physicians -- at different stages of implementing precision medicine are faced with managing the pace at which coverage is provided and informing patients of their responsibility. This complexity may carry over into decision making at the clinical level and must be explored in the interviews.
Finally, there is added ambiguity for providers:
The other conflicting influence is that new but initially expensive tests appear that do impose a financial burden but, with dubious evidence for their effectiveness or cost effectiveness, are generally not covered. Thus, there is likely to be continued debate on how insurance should deal with both the testing and treatment associated with personalized medicine (Pauly 2019).
This ambiguity’s impact on adoption of precision medicine will be probed in the Study 2 interviews.
Measuring the Potential Health Impact of Precision Medicine. Hult (2019) declares that the potential of precision medicine derives from either its ability to create treatments for use across a heterogeneous population or from providing information that can optimize the outcome of existing treatment. His study focused on the magnitude of the latter effect on treatment of patients with multiple sclerosis. Hult (2019) has wide-ranging conclusions:
Personalized medicine has a greater potential health impact when treatment effects are less correlated across treatments, the variance of the distribution of health impacts is larger, there is less
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noise in an individual’s signal of their treatment effect, and there are more treatment options (Hult, 2019).
An extension of this work that will be probed in the interviews is whether physicians see precision medicine providing some advantage for the assessment of alternative treatments,
especially when prescribing pharmaceuticals that are second generation entrants or are
believed to have only an incremental effect. When interviewing physicians for Study 2, their
interpretation of precision medicine’s utility across different clinical settings, circumstances
and applications will be explored.
Precision Medicine Development in a Global Context
At this stage in the history of precision medicine, attempts to estimate current
sales of products or services that can be broadly defined as relevant are at best imprecise,
as it were. Tracking trends and predicting demand is equally hazardous. The common
reasons are that product and service definitions are still in flux, and there is limited data
on what is being sold, to whom and for what price. With those cautions in mind it is valuable nevertheless to attempt to corral major movements on a regional basis and
determine possible latent demand or potential industry earnings. The purpose of such an
effort in the context of this dissertation is to continue building the case that precision
medicine can include among its appeals an economics that justifies research and
development, product distribution and support, and efforts to integrate precision medicine
into the health care milieu. The source of the data is a hardcopy publication by Philip M.
Parker offering: “The 2020 – 2025 World Outlook for Precision Medicine” (Parker,
2019). Parker’s efforts are bold but are currently the only attempt to characterize sales by
countries or regions and forecast demand. The overall thrust of the work supports this
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dissertation’s position that precision medicine is an emerging distinguishable force in
health care and if economic opportunity is a driver, there will be a continual flow of
products and services to satisfy demand.
The definitions and methodology used by Parker (2019) are not mere research
conveniences but are rooted in economic theory and medical decision frameworks. The
study defines “the sales of precision medicine as including all commonly understood products falling within this broad category, such as big data analytic, bioinformatic, gene sequencing, drug discovery, companion diagnostic technologies and medicine used in oncology, immunology, respiratory, and central nervous systems, irrespective of product packaging, formulation, size or form” (Parker, 2019). That said, the report cautions that it does not report “actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the countries of the world)” (Parker, 2019).
Parker (2019) gives estimates for the worldwide latent demand for precision medicine. Latency, as used, refers to what is not yet realized whereas demand is the notion of an economic quantity “that a target population or market requires under different assumptions of price, quality and distribution.” Most importantly for purposes of this dissertation, “latent demand, therefore, is commonly defined by economists as the industry earnings of a market when that market becomes accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E) or total revenues (not profit) if a market is served in an efficient manner.” Parker’s (2019) latent demand for precision medicine is not actual, historic, or future sales. His methodology and data essentially provide a relative ranking of demand. Parker relied on a variety of sources, including excerpts and data from the World Bank, the US Department
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of Commerce, the US State Department, and various national and other multilateral
sources.
Based on this approach, Parker’s (2019) latent demand for precision medicine is
estimated to be US$ 53.6 billion in 2020. This demand, not surprisingly given the
existing worldwide consumption of health care, is not evenly distributed across regions.
Asia is the largest market with US$ 23.7 billion or 44.25 percent, followed by North
America (including the Caribbean) with US$ 11.2 billion or 20.91 percent. Europe
follows with US$ 11.1 billion or 20.76 percent of the world market. These three regions
cover nearly 80% of global latent demand for precision medicine. The methodology
produces proportions roughly representative of health care expenditures worldwide,
although in Table 12 Africa and Oceania are higher than their current share of
expenditures. One conclusion, which will be explored at length in Study 2, is that
precision medicine may further exacerbate global health inequity and that planning to
avoid that scenario must begin now.
What does Table 12 suggest about precision medicine within the context of global
demand? In the case of the US, Europe and selected Asian countries, precision medicine
will roughly and proportionally track demand for health care generally. By contrast,
Africa currently absorbs about 1% of the worldwide health care expenditure whereas its
latent demand as determined by Parker (2019) is at least four times higher. Of that
demand, half is represented in just four countries: South Africa, Egypt, Nigeria, and
Algeria. The analysis does not consider the movement among African countries towards
universal health coverage. Suffice it to say, early indications of sales that fall into
Parker’s (2019) definition of precision medicine are suggestive that global demand will
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Table 12. Worldwide Market Potential for Precision Medicine in (US $ millions) by 2020 Region US $ millions % of Globe Corresponding Population % Asia including Middle 23,700.79 44.25 59.5 % East North America and 11, 195.82 20.91 5.4 % Caribbean Europe 11,119.80 20.76 9.8%
South America 4,534.97 8.47 8 %
Africa 2,283.13 4.26 16.8 %
Oceania 719.77 1.34 0.5 %
Totals 53.6 100% 100%
Source: Derived from Parker 2019. Source: Corresponding population % added by author to illustrate disparities from World Bank data.
be abundant. Again, the latent demand calculations are not meant to represent actual revenues, but a broad interpretation is that the framed US$ 53 billion would constitute roughly 10% of global pharmaceutical sales. Patient care and service allocations are not part of the analysis. In other words, precision medicine is already positioned to play a predominant role in health care in the foreseeable future in terms of latent demand. How this will be monetized is at present anyone’s guess, but the point is that precision medicine is visible and potentially forceful.
QED: Precision Medicine as a Paradigm Shift Invites Resistance
The second argument of this dissertation is that resistance to precision medicine is essentially resistance to the Molecular/Genetics Paradigm shift. This is imprecise because this paradigm shift is embodied in practice and is the basis for scientific and commercial progress. As argued in Chapter 1, however, prevailing paradigms can coexist with paradigm shifts. This dissertation has characterized the Precision Medicine Paradigm as
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the clinical culmination of the Molecular/Genetics Paradigm shift; precision medicine
essentially is forcing the re-thinking and reclassification of disease, i.e., the pathologic
foundations of medicine. While clinicians easily accept new insights into the state of
disease, there is a tipping point where the conception of disease and therapeutic strategies
become insecure. Where genetics does play a role in disease, clinicians readily accept the
scientific underpinnings, but when dealing with a single patient for whom genetics plays
a role in illness, there can be a reluctance because the interventional tools are still works-
in-progress. Consider the relationship of a clinician to a pathology or laboratory report in
the current environment. The education of a physician is based on comprehensive
diagnosis and the interpretation of data. Precision medicine, being at an early point in its history, provides a new data set that the clinician either is not ready to interpret or, once interpreted by others, must formulate a treatment strategy that is outside conventional standards of practice or guidelines.
An example is the management of tumors. Unlike in the past, tumors are characterized prior to their removal; tissue harvesting is made possible by imaging- guided technologies. Clinicians together with pathologists share in the information acquired thus allowing a wider range of treatment decisions. Diagnostics associated with precision medicine provide more accurate prognostication and prediction of response to treatment. When surgical intervention is the prevailing standard of care, the new information may divert from that strategy. Given that information from various tests must
be integrated like never before, the role of the pathologist has changed from being the
passive characterizer of a disease to an active participant in clinical decision making.
The role of pathology and the pathologist, therefore, moves squarely into the
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clinical arena. Given the complexity of information that must now be processed, there is a
change in practice patterns. Putting aside the traditional independence that physicians
have in making decisions for their patients as a basis of resistance, the expanded decision
framework can be threatening.
A Conclusion of Study 1: Summary of Evidence for a Paradigm Shift
Precision medicine represents a true paradigm shift in the history of medicine
with the precipitating crisis being the current imprecision with which medicines are selected and prescribed. Resources are limited throughout the world and the trial and error attempts at finding the right pharmaceutical at the right time is an enormous inefficiency as well as a basis for unnecessary suffering for the patients. The underlying science of precision medicine in historical terms is a radical departure from the disease modeling and staging that prevailed throughout the 20th century. Its implementation is
also a cataclysmic shift away from the population-based statistical determinism that has
driven medical decision making for generations. Medical practice can now move away
from one-size-fits-all, trial-and-error experimentation towards a targeted approach based
on patients’ molecular information. This approach better informs therapeutic strategies.
Such a transformation, however, demands a global collaborative effort to absorb the pace
of scientific and technological progress. Of course, progress in the direction of precision
medicine is subject to additional constraints, including regulatory regimes,
reimbursement constraints and the always elusive development of clinical standards of
practice.
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Study 2 will probe these issues more deeply during the interviews including the thesis here that the foundation for precision medicine as a paradigm shift is the transformation of the concept of disease that is underway. Moreover, there is an evolving expanded role of specialist physicians and genetic counsellors in supporting the patient’s attending or primary care physician. Haspell et al (2010) emphasize the shifting role of pathologists in providing patient care:
Genomics and “medical sequencing” will revolutionize clinical laboratory diagnostics as the foundation for the new era of personalized medicine. However, the medical profession lags far behind the technology and business communities in recognizing and preparing for this change. Pathologists must take the lead in the application of genomics technologies, including whole-genome sequencing, to laboratory diagnostics and personalized medicine. As a critical first step in leading this change, we have established a first-in-the-nation resident curriculum in genomics and personalized medicine. Our goal is to catalyze the adoption of similar training modules in every pathology residency in North America. If we succeed in the widespread implementation of this type of training as a core competency in pathology, we will ensure that the discipline of pathology will lead rather than follow in the coming era of personalized medicine (Haspell et al, 2010).
When physician specialties recognize the need to re-structure the core training of their field, that is strong evidence that the community recognizes and accepts a paradigm shift as imminent.
A further piece of evidence is the establishment of the Pharmacogenomics
Knowledgebase (PharmGKB), a resource that collects, curates, and disseminates information about the impact of human genetic variation on drug responses. “The data base provides clinically relevant information, including dosing guidelines, annotated drug labels, and potentially actionable gene–drug associations and genotype–phenotype relationships. Curators assign levels of evidence to variant–drug associations using well- defined criteria based on careful literature review. Thus, PharmGKB is a useful source of
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high-quality information supporting personalized medicine–implementation projects
(Whirl-Carillo, 2013).” The specialty of pharmacology also recognizes the apparent paradigm shift.
Gameiro et al (2018) argue for an integrated, cross-institution approach to the
building of precision medicine. They argue:
that the development of algorithms to predict and treat diseases based on a subpopulation-specific set of characteristics, such as genetics, drug responses, lifestyles, and social demands, requires a vast amount of information. Thus, instead of performing a series of separate and independent research protocols, initiatives aiming to create and integrate data from different medical centers are necessary. Using currently available tools, such as cloud computing, artificial intelligence, and big data, the collection and analysis of different databases will allow the creation of algorithms to direct clinical practice (Gameiro et al, 2018).
The advocacy for this approach for the delivery of medicine is perhaps the strongest
evidence of all that precision medicine is a paradigm shift.
Is there Resistance to the Normal Science of the Molecular Period?
A logical next question in this inquiry is whether there is resistance to the Normal
Science of the Molecular Period. In the context of this study, this is really two questions.
The first concerns whether the scientific basis of precision medicine is proceeding apace.
It is, as will be explained. The second question concerns whether precision medicine has
emerged or is emerging as the new normal medicine. It has not, as will be explained.
Normal Science in the Kuhnian universe is the yeoman work of scientists as they
theorize, observe, and experiment within the prevailing paradigm. Kuhn regarded science
as solving puzzles and explained that normal science accumulates detail consistent with
established theory but not questioning or challenging that theory. Applying the normal
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science concept to biology is inherently hazardous because the nature of biological
research is discovery oriented and interdisciplinary; dogma theoretically yields to new
observations that once validated and accumulated are persuasive. While the normal biologist presumes that all values, techniques, and theories falling within the expectations
of the prevailing paradigm are accurate, there is a constant alertness for variance. This
intellectual volatility derives from the nature of what is being studied. Biological systems
are dynamic and are influenced by epigenetic and environmental changes. Biology at its
best is alert for variances and changes in systems. In contrast to the physical sciences,
biology is built around discovery and documentation of phenomena, albeit minute, but by
armies of investigators in universities, institutes, and companies on a global basis.
Ordinarily, Kuhn believed that the bulk of scientific inquiry was normal as
scientists pursued refining the paradigm, identifying, and evaluating facts that reinforced
the paradigm and, finally, testing those new observations that either support the
theoretical paradigm or open it to empirical reappraisal.
Theorization loosely follows the diagram in Figure 14. Scientists derive rules
from paradigms, which provides a framework for rationalizing values, methods, and
theories that constitute the scientific commons of a field. Normal Science’s energies are
directed at improving the alignment of predictions based on a paradigm and the facts
identified from investigation within the context of that paradigm; normal science does not
aim to discover new phenomena in the physical sciences.
Biology may be different because it can be characterized by anomalies which
represent challenges to be solved within the prevailing paradigm. Only if an anomaly or
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Pre- or Peripheral Science Pre-Paradigm
Normal Science Paradigm Shift
Model The Kuhn Cycle Drift Model Revolution
Model Crisis
Figure 14: The Kuhn Cycle as derived from a reading of Kuhn by author. series of anomalies resists successful reconciliation over time and for a preponderance of members of a scientific field will a paradigm come under challenge during what Kuhn would deem a crisis of normal science. Anomalies are a constant of the dynamics of living systems, but rarely rise to a crisis point because they often can be reconciled or cordoned off from the mainstream as unique artefacts. This may be one factor as to why biology proceeds in a different way and at a different pace relative to other sciences.
When the scientific community does embrace a new set of expectations and theories that govern the work of normal science the change rises to that of a scientific revolution. Ordinarily, successive paradigms replace each other and are necessarily incompatible with each other, but in life sciences, they often can coexist because there are many disciplinary approaches to biology, e.g., biochemistry, genetics, microbiology, virology, physics, mathematics, and complex systems theory.
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The question, “Is there a normal science of molecular biology?” can be answered
in a way that is both flip and accurate: “Sure, there are lots of normal sciences.” To
capture the wisdom and humor of this statement, a capsule history of the origins of
molecular biology is helpful.
Molecular biology is the study of living things at the level of the molecules which
control them and make them up. While traditional biology concentrated on studying
whole living organisms and how they interact within populations (the morphological or
“top down” approach described earlier in this Study), molecular biology strives to
understand living things by examining the components that make them up (the molecular or “bottom up” approach also described earlier in this study). Both approaches to biology are equally valid – complementary rather than competing normal sciences – although improvements to technology have permitted scientists to concentrate more on the molecules of life in recent decades. Molecular biology as currently understood originated
in the 1930s through the convergence of the distinct biological and physical disciplines –
biochemistry, genetics, microbiology, virology, physics, mathematics, and complex
systems theory – listed above. Molecular biology chiefly concerns itself with
understanding the interactions between the various systems of a cell, including the
interrelationship of DNA, RNA, and protein synthesis, and learning how these
interactions are regulated. Molecular biology’s goal is to explain the phenomena of life starting from these two categories of macromolecules: DNA/RNA (nucleic acids) and proteins which are the active agents of living organisms. In its most basic portrayal, the molecular revolution’s scope is to characterize the structure, function, and relationships between these two types of macromolecules. Molecular biology provides scientists with
Page 151 | 477 the framework necessary to understand the interactions of life’s components. Scientists can use the tools to determine the function of single genes or proteins and determine the consequences when a gene or protein is absent or faulty – thus providing a mechanism for redefining disease. Specifically, molecular biology examines when and why certain genes are switched activated or inactivated. Insight into these factors provides a deeper understanding of how organisms work, and knowledge for developing treatments when living things are not functioning optimally. As suggested above, there are numerous normal sciences within molecular biology.
Summary of Conclusions of Study 1
Recounting the history of the series of discoveries made under the normal science of molecular biology is well beyond the scope of this study. The fact of the matter is that from its origins in the mid-20th century until now, the Molecular Period has proceeded unabated and while there is ever present alertness for crises that might precipitate development of a new paradigm, e.g. vigilance surrounding the reductionist and determinist milieu that currently prevails in genetic science, the central dogma endures.
The central dogma was articulated in 1957 by Francis Crick (1958) who foretold the relationship between DNA, RNA, and proteins, and articulated the "sequence hypothesis." The DNA structure work published in 1953 postulated a replication mechanism which was confirmed by Meselson–Stahl (1958). In combination with the work of Crick and colleagues, scientists demonstrated that the genetic code was based on non-overlapping triplets of bases, called codons. These findings represent the birth of molecular biology, particularly biotechnology. This was the slate on which the normal
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science of molecular biology was sketched, and the biotechnology industry was built. The
normal science of molecular biology has proceeded with trillions of dollars of public and private support over the last 70 years (Chakma et al, 2014).
There is no resistance to the normal science of the Molecular Paradigm, but there
is philosophical concern about its growing and apparent limitations as an epistemology of
life. There is no resistance to the molecular and genetic foundations of precision medicine
either. There is, however, resistance to the incorporation of precision medicine into
clinical practice for the many reasons articulated throughout this manuscript which will
be further studied in Study 2.
This chapter can be concluded through Ciardiello et al (2016) who offered an
analysis from a clinical and patient perspective on awareness, understanding and adoption
of precision medicine for personalized treatment of cancer patients. Their analysis
focused primarily on the use of biomarkers, but the findings have broad significance. The
investigators conducted two separate multinational surveys of oncologists and patients
with cancer. The purpose was to assess the awareness and use of biomarkers in clinical
practice. Their data explored the self-reported and physician-assessed levels of patient
cancer literacy and factors affecting physicians’ choice to use biomarkers in treatment decisions. They interviewed 895 physicians and 811 patients. Most patients and physicians reported that patients understood that a tumor could be tested to determine what treatment would be most effective (78% and 73%, respectively) and that patients
would be willing to participate in a personalized treatment plan. Whereas 85% of patients
felt that they understood their treatment when it was explained to them, only 23% of
doctors felt that their patients were always fully informed. Most physicians (90%)
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reported using biomarkers; among the 10% not performing biomarker analysis, the most
cited obstacles were local availability, speed of obtaining results, and cost. These data
demonstrate wide global use of biomarker testing but with regional variations reflecting
cultural and local practice. Self-reported and physician-assessed cancer literacy, although
generally high, highlighted important regional variations and the need to provide patients with additional information. These findings support some of the observations of the
Pritchard et al (2017) work, but still do not probe the organizational dynamics of precision medicine adoption and movements towards the establishment of clinical practice standards – the objectives of Study 2 which will be realized through the analysis of interviews with three of the leading integrated precision medicine programs.
Transition from Study 1 to Study 2
There is deliberate asymmetry in the design of Studies 1 and 2. Specifically, this manuscript’s approach to resistance to precision medicine and successful implementation of precision medicine are posed differently in Studies 1 and 2. Whereas the primary focus of
Study 1 is on the environmental factors that lead to success of precision medicine, the secondary focus is on the policy nature of resistance to precision medicine as currently portrayed in the literature. Study 2 reverses that emphasis.
Study 1 developed an historical envelope around the genesis of precision medicine, why it represents a Kuhnian paradigm shift, why paradigm shifts despite their revolutionary nature require time to convert scientists, how the progress of science inevitably led to precision medicine, and what constitutes parameters for successful implementation. Study 1 then continued with challenging and expanding the prevailing explanations to the climate of
Page 154 | 477 resistance and offers reasons why these explanations must be extended into inquiries about the organizational and community of practice dynamics of resistance – phenomena currently overlooked in the literature.
By contrast, the thrust of Study 2’s thesis centers on the factors that lead to resistance in communities of practice in both general organizational environments and in health care settings. This serves as the backdrop to the analysis of three leading institutions which through their success demonstrate that resistance can be overcome with planning and execution of reproducible specific measures. These measures form the underpinnings of the
Findings and the Propositions of Study 2 which, therefore, provide an explicit pathway for overcoming resistance and duplicating the success of the three institutions.
[END OF STUDY 1]
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CHAPTER 3
(STUDY 2): AN EXPLORATION OF PROVIDER ORGANIZATIONAL AND DECISION DYNAMIC READINESS FOR PRECISION MEDICINE IN THE UNITED STATES
Introduction to Study 2: Paradigm Shifts and Resistance to Change in Scientific and Medical Practice
Study 1 made a manifold case that there is resistance to the full incorporation of precision medicine into medical practice. The basis for Study 1 is that there have been relatively few paradigm shifts in the life sciences and medicine that satisfy the concepts developed in Kuhn’s Structure of Scientific Revolutions (1962) and that the failure to consider the impact of a true paradigm shift on medical practice abets the phenomenon of resistance. This study’s embrace of “paradigm shifts” adheres to the Kuhnian criteria and not the casual use of the term that is often applied whenever a field adopts a new, radical but practical approach of addressing its mission or problems. Paradigm shifts, in the
Kuhnian sense, occur when new insights arise that change the fundamental thought processes, cosmology and epistemology of a field of inquiry. Such intellectual leaps typically meet profound resistance over extended periods as science and technology assimilates the new processes and reconciles the new ways of thinking with the old constructs or else eschews the old constructs. The transition to a new normal science or normal practice is punctuated. It is not seamless.
One of the medical paradigm shifts that meets Kuhn’s criteria was dubbed in
Study 1 as the Molecular Paradigm of which precision medicine is a trailing manifestation, i.e., it is the practical clinical enablement of the insights and teachings of the Molecular Paradigm. A central tenet of Study 1’s argument is that historically there
Page 156 | 477 is a resistance to the incorporation of a paradigm shift into prevailing normal science or normal professional practice because the fundamental epistemology has been altered, and the frameworks for scientific activity are interrupted. Study 1 makes a case that over the last 75 years, the pharmaceutical Synthetic Period and biological Molecular Period are coexisting and cross-pollenating during the era that the full impact of the Molecular
Paradigm is fully assimilated into medical science and practice by all active generations of practitioners, a process that may take another 25 years or more.
In order to support that there is resistance to the adoption of precision medicine,
Study 1 cited the study of Pritchard et al (2017) which enumerated the social, economic, and structural challenges that must be overcome. Furthermore, Study 1 also established that there is a crisis in the current medical care paradigm in the form of the hit and miss nature of pharmaceutical response rates faced by clinicians when selecting and planning a therapeutic strategy. Kuhnian paradigm shifts necessarily are provoked by an intellectual or practice crisis; such a crisis exists in medical practice.
Progress in areas of public policy and regulatory oversight of the products and practices associated with precision medicine was detailed and supported by providing an inventory of approved products and their uses. Study 1 addressed most arguments that the science and technology of precision medicine are insufficient or unprepared to support full scale clinical practice not only through the exhaustive inventory of currently available approved precision medicines and companion diagnostics, but with an additional compendium of precision pharmaceuticals and companion diagnostics in the global development and regulatory pipeline.
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While it is the case that regulators internationally seek to create standards and systems going forward to accommodate the pace of precision medicine developments, the record of existing approvals underscores the progress made. Indeed, in 2019, 42 percent of the 48 new molecular entities approved by the United States Food and Drug
Administration are precision medicines (Jarvis, 2020). Finally, in Study 1 the complex
nature of economists’ objections and payers’ concerns on reimbursement related to
precision medicine were acknowledged and explained as persistent obstacles but with a
path laid for their further resolution during the current period when precision medicines
are approved by regulators and hospital charges reimbursed by payers.
A reasonable conclusion of the Study 1 exercise, therefore, is that any posited
macro-level explanations of resistance to precision medicine – lack of pharmaceutical
products or diagnostic tools, hostile economics or reimbursement, or resistant regulatory
regimes – have been resolved or are on a pathway towards resolution. The issues no
longer justify material resistance by health care provider institutions and clinicians. This
state of affairs necessarily leads to a conclusion that resistance must rest at the
organizational and physician practice levels and that such resistance is a manifestation of
the adjustment to the Molecular Period paradigm shift, i.e., that precision medicine
challenges the normal science of the Synthetic Period, interrupts patient care systems in
hospitals, prevailing clinical practice patterns, the patient care journey, and approaches to
defining, diagnosing and treating disease.
More fundamentally, as was established in Study 1, the basic understanding of the
nature of disease has shifted from observation of aberrant morphological phenomena to
pathologic molecular processes. Study 2 establishes – within a context of the dynamics of
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communities of practice – the literature framework for resistance to change in
organizations generally and in health care settings in particular and explores how three
leading institutions have dealt with this resistance to establish fully integrated and
operational precision medicine programs and overcome the negative consequences of the
Molecular Period paradigm shift.
Study 2 Objectives: Exploring Organizational Antecedents and Dynamics at Providers Deeply Engaged in Precision Medicine – The Significance of this Research
In order to set the stage for the importance and uniqueness of Study 2’s objectives
the author can share preliminary results from a parallel study in which he is involved. The
author fortunately has access to data for a study in progress which will not be published
until mid-2020. Specifically, this author is on the Steering Committee for a research
project underway by the Personalized Medicine Coalition (PMC):
The Personalized Medicine Coalition (PMC), representing innovators, scientists, patients, providers and payers, promotes the understanding and adoption of personalized medicine concepts, services, and products to benefit patients and the health system. Believing that paradigm shifts, especially in medicine, do not happen just because the science and new technologies suggest they should, PMC supports investment in and adoption of personalized medicine through education, advocacy, and evidence development (PMC, 2020).
This author, however, can share only those results that were presented in an unpublished
summary slide presentation delivered by the consultancy engaged to conduct the study –
Health Advances (2019) – to the audience of the 15th Personalized Medicine Coalition
Conference on November 13 – 14, 2019 at Harvard Medical School.
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The PMC Landscape Study (hereafter, “Landscape Study”) is focused on the
landscape of precision/personalized medicine adoption in the United States, i.e., a
detailed census of active institutions and their respective stages of implementation of precision medicine. The Landscape Study is designed as a detailed survey of the level
and scope of personalized medicine activities and not an analysis of the organizational
dynamics of the institutions reporting their activity, or the attitudes of physicians engaged
at these institutions. The Harvard presentation provided the following: (a) the PMC methodology, (b) the criteria used to determine the degree of personalized medicine
activity, and (c) the level at which the participating institutions are operating. This author
was involved in a team effort on the original study design, collection of data, the current
analysis of data, and will ultimately be involved in the review of the manuscript for
publication (but not co-authorship) which is scheduled for submission during the first half
of 2020. The thesis of the Landscape Study can be characterized as:
Organizations in the US have recognized the value of PM and are integrating it in clinical care, with oncology continuing to lead the way. However, there is still a way to go before we can call the US ‘fully integrated,’ and organizations can vary widely on their approach to PM integration. A consistent framework on which to evaluate organizations and their progression over time can help to inform planning of initiatives to continue supporting advancement of PM in the near- and long-term (Health Advances 2019).
The data gathered thus far is through a thorough national survey of health
providers (hospitals and hospital systems) to which 156 health providers representing
academic and community hospitals responded. This number represents a self-selected
sample of a much larger national invitation for participation. This is itself suggestive of
resistance across the medical community; there are over 6000 hospitals in the United
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States that comprise hundreds of integrated systems. The 156 providers – individual hospitals or hospital systems – that responded to the survey participated voluntarily.
There is, however, a significant sample bias in that institutions not engaged in precision medicine most likely opted out. This assertion has not yet been validated through follow- up calls with non-participating institutions but based on an examination of the identities of the institutions that did choose to participate, there appears to be robust correlation with institutions known through the medical literature, participation at conferences and membership in the PMC to be engaged in some level of precision medicine adoption.
The premises of the PMC Landscape Study are that there is a national dispersion of stakeholders championing precision medicine at a cross-section of institutions. These are specifically clinicians, organizational and opinion leaders, and payers who recognize the value of the precision medicine approach and who are encouraging widespread use in clinical management. Generally, at participating institutions implementation started in testing biomarkers for oncology and expanded at a different pace across other clinical areas and through the continuum of care. The drivers for implementation are universally the desire to improve quality of care outcomes and reduction of the costs of care (Health
Advances, 2019).
For the Landscape Study, Health Advances – an independent health management research consultancy – together with the study Steering Committee established eight criteria for determining the level of maturity of engagement in precision medicine. The criteria were postulated through extensive discussions between the Steering Committee and Health Advances with challenges and refinement made through Delphi consensus building (Dalkey, 1963; Brown, 1968). The criteria applied are:
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1. Collection of genomic data wherein physicians are ordering both targeted and
broad genetic testing. Whole Exome Sequencing (WES) and Whole Genome
Sequencing (WGS) are most common for oncology and rare/undiagnosed
diseases.
2. Collection of other “omics” data wherein physicians consistently order other
types of testing for personalized medicine beyond solely genetics.
3. Collection of non-laboratory data whereby providers are collecting at least one
type of non-laboratory data, such as social determinants of health, to enable
personalized medicine.
4. Testing guidance and data accessibility whereby full integration of testing
recommendations and results are integrated into the electronic health records.
5. Utilization of data especially for more established clinical areas such as oncology
and prenatal testing where the focus is on collecting actionable data. Other areas
are typically more experimental.
6. Data sharing across clinical areas. Respondents indicated that personalized
medicine data is primarily shared internally. Few organizations share data
externally.
7. Internal precision medicine leadership where there is an identifiable focal point
and promoter of precision medicine in an organization and accompanying change
agents, and a definable nature of authority.
8. Funding of precision medicine where there is reimbursement of testing in more
established areas, such as oncology and prenatal/neonatal care, and emerging
models for other areas.
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The preliminary capture and analysis of data was used to classify the 156 responding institutions into five levels of adoption:
Level One: Individual physician adoption on a limited basis with significant
variation among clinicians with little to no organizational support. Fifteen
(15) percent of the responding organizations fit into this level.
Level Two: Individual or group adoption but with little to no support from
institutional leadership, including testing guidance and data utilization or
sharing. In this level there is significant variation in clinical use in the
organization. Thirty-one (31) percent of responding organizations fit into
this level.
Level Three: Inconsistent but strong use of precision medicine in one or two areas
such as genomic data collection, testing, guidance, data utilization or data
sharing. Thirty-two (32) percent of respondents fit into this level.
Level Four: Strong data collection with consistency for genomic as well as
clinical/economic outcomes data with a heavy focus on use of data for
research. At this level there is some inconsistency around data access and
sharing, and leadership support. Nineteen percent (19) of respondents fit
into this level.
Level Five: Expansive data collection likely including WES/WGS, broad other
omics data, clinical and economic outcomes data across all physicians,
forward thinking data sharing, and committed leadership and funding.
Only three percent (3) of respondents (four institutions) fit into this level.
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As of this writing, the identity of the four institutions that comprise Level Five
has not been disclosed to the Steering Committee by Health Advances as a means of avoiding informal discussions and influence of the interpretation of the data. The current
plan is to keep the identities of the participating institutions blinded even upon
publication with the expectation that participating institutions can place or rank
themselves based on the description of the eight activity-classification criteria and the
five levels of implementation that will be described once the publication is released.
Based on an independent appraisal using the same criteria and based on reports in the literature and peer-reviewed publication, this author was able to identify with high confidence three of the four institutions comprising Level Five, each of which consented to participate in the research of this dissertation. For reasons of requested anonymity by some of the institutions these are identified as Alpha, Beta and Gamma. Based on reports
in peer-reviewed literature, these three institutions meet all the Level Five criteria
(Williams et al 2018; Carey et al 2016; Nadauld et al 2018; Haslem et al 2018; Volpi et al
2018).
The goal of the Landscape Study is that, once published, hospitals can interrogate their own unique precision medicine adoption profile against the aggregated data in order to highlight specific challenges and potential solutions that may be insightful for that provider organization to plan future strategic initiatives to reach Level Five. The Steering
Committee postulated that the data will be helpful for industry stakeholders to identify individual solutions for health systems based on their unique deficiencies in an overall attempt to accelerate precision medicine adoption moving forward. The framework should also be helpful for institutions to identify their own deficiencies, providing data
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for the internal champions to take to their institutional leadership and clinical colleagues
to bring about improvements, robust clinical adoption, fully integrated implementation of
precision medicine and ideally a higher rating on the progress towards implementation scale.
The current Landscape Study, however, will not include deeper probing into the organizational antecedents and dynamics at the Level Five institutions, let alone at any of
the other levels, although discussion about the research objectives of this dissertation
within the Steering Committee appear to be provoking interest in such investigation on a
broader scale in the future. This Study 2 represents a first effort at analysis of the organizational antecedents of precision medicine implementation by exploring the who,
what, when, where and why the institutions Alpha, Beta and Gamma characterize the
leadership in precision medicine.
This investigation also contributes a description of the implications of the three
focus institutions’ structure and models for organizational adoption of precision medicine
elsewhere. Moreover, the peculiarities of precision medicine adoption disclosed in this
study may suggest new concepts in the corpus of organizational theory that focuses on
resistance to change.
Study 2 now drives towards conclusions for the following:1) establishment of
antecedent conditions for implementation of precision medicine; 2) determination of
requirements for acceleration of precision medicine at an organizational level; 3)
postulation and interpretation of metrics for determination of impact of precision
medicine within an institution; 4) approaches to the reconciliation of the different
business models of the stakeholders in precision medicine, i.e., the comprehensive joint-
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clinic model of care versus the disseminated contract model of care; 5) implications of
the antecedents to precision medicine to organizational theories of change; 6)
implications for organizational theory surrounding formulation of clinical standards; and,
7) implications for organizational theory related to resistance to change, especially to
historic paradigm shifts.
Literature Reviews: Theory Addressing Resistance to Change
Defining the concept of change: organizations versus communities of practice
In the literature, defining change is often treated in the common sense of the
word. Furthermore, “resistance to change” is similarly treated. This practice is
unfortunate because the notion of change is itself an evolving definition. For the purposes
of this study, the prevailing definitions of change are not congruent with the challenges of
change associated with the Kuhnian concept of the paradigm shift as espoused in Study 1.
In fact, the role of this study in expanding the literature of change and in informing
approaches to treating resistance to change rely heavily on distinguishing the notions of
change and contrasting them with the changes associated with a Kuhnian paradigm shift.
Precision medicine as a paradigm shift has been underway for 75 years and will still be a work in progress for another one or two generations of physicians. As an object of the study of change, it is irrelevant to those definitions of change that are framed in static terms, or in ways that abbreviate the dynamism of change. Or especially, to theories that overlook that medicine, and in particular its specialties, are communities of practice.
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The change literature, moreover, addresses change within group or organizational
contexts. Although precision medicine is delivered within the context of hospital systems
as organizations, as a paradigm shift it provokes change in medical practice and within or
among communities of practice. Communities of practice do not function the same way
as traditional organizations. What is a “community of practice”? Lave and Wenger
(1991) introduced a theory that emphasizes the social nature of learning. Initially, the focus was on business and management but linked the concept to medicine and medical education in 2002 (Parboosingh 2002).
Definitions vary, but a community of practice as “a persistent, sustaining social network of individuals who share and develop an overlapping knowledge base, set of beliefs, values, history and experiences focused on a common practice and/or mutual enterprise” (Barab 2002) is a definition that relates well to the practice of medicine.
The transition from viewing medicine as a community that has long been characterized by collegiality and morality to the concept of medicine as a community of practice in which learning takes place has an inherent logic. The cultural, structural, and behavioral aspects of a collegial profession as well as its moral base become parts of the norms of practice (Cruess et al 2018).
Brown & Duguid (1991) describe studies that demonstrate that “workplace practices indicate that the ways people actually work usually differ fundamentally from the ways organizations describe that work in manuals, training programs, organization charts, and job descriptions,” despite the fact that organizations rely on these materials to improve work practices. “Working, learning, and innovating are closely related forms of human activity that are conventionally thought to conflict with each other,” Brown &
Duguid (1991) add. The source of opposition, they observe, lies in the “gulf between
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precepts and practice.” They suggest “that practice is central to understanding work.
Abstractions detached from practice distort or obscure intricacies of that practice (Brown
& Duguid, 1991).
Brown & Duguid (1991) cite Orr’s ethnographic studies (Orr, 1990a, 1990
b, 1987a, 1987b) to “illustrate how an organization’s view of work can overlook
and even oppose what and who it takes to get a job done.” Brown & Duguid
(1991) make the more general claim that reliance on espoused practice, which
they refer to as canonical practice, can bind an organization’s core to the actual
and usually valuable practices of its members, including such noncanonical
practices as workarounds. “It is the actual practices, however, that determine the success or failure of organizations” (Brown & Duguid, 1991).
In the case of precision medicine, this is an important point because of the existing tension between the administrative preferences of an institutional provider and the way physicians practice medicine. Physicians ultimately are autonomous decision makers on applying diagnosis to a course of therapy, but they characteristically do so with reference to standards of practice that are developed and promulgated by their specialty community of practice. There are
potentially dueling standards of practice between the organization and the
community which can be manifest as differences in pace of adoption or inclusion
of prescribed methods or therapies.
This point is supported by the convergence of Lave and Wenger (1990)
with the Brown & Duguid (1991) study. The latter build’s on the former’s theory
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of learning as “legitimate peripheral participation in communities of practice.”
They further observe:
Much conventional learning theory, including that implicit in most training courses, tends to endorse the valuation of abstract knowledge over actual practice and as a result to separate learning from working and, more significantly, learners from workers. Together Lave and Wenger's analysis and Orr's empirical investigation indicate that this knowledge-practice separation is unsound, both in theory and in practice. We argue that the composite concept of "learning-in-working" best represents the fluid evolution of learning through practice (Brown and Duguid, 1991).
Brown & Duguid (1991) further emphasize “through their constant adapting to
changing membership and changing circumstances, evolving communities of
practice are significant sites of innovating.”
The implied tension here is arguably a causal factor in resistance to precision medicine by the physician specialty communities of practice. While it may be a cliché, medicine is an art and a science. Personal professional insights are accumulated over time as experience is processed by each physician and then compared to the standards of practice set forth by the community of practice.
Clinical judgement then adjusts to the synthesis of personal experience to the community’s standards of practice. It is this dynamic that is a source of innovation in medical practice. It is a dynamic that is suspicious of how a presumed paradigm shift potentially conflicts with norms or inhibits innovative practice. The paradigm shift must become integrated into the existing community
or communities of practice in order to be embraced as a new normal art or new
normal science.
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This tension is further exacerbated by the roles of a group of physicians serving as managers or leaders, and those who are in practice (either in sole practice or as part of an integrated clinic structure). Mudambi and Swift (2009) observe that “scientists and managers belong to different ‘professional guilds,’ subscribing to different belief systems and valuing different types of incentives.
These differences give rise to tension between scientists and managers.” In the matter of precision medicine, it might be argued, the advocates (the managers) and practitioners (the scientists) are both physicians, thus the tension should be de minimis. On the contrary, differences may be aggravated by the contrast of roles.
In technology intensive organizations, it is the scientist promoted to manager who manages other scientists. The physicians serving these different roles may derive from the same community of practice, but in their respective roles they represent different guilds. The impact of these tensions will be elaborated further in the final section of this study: “Incongruities with Organizational Theory.”
Professionals, particularly in medicine, assume a group identity by moving from participation on the periphery of the profession, say during training, to full membership through acquisition of requisite knowledge and skills within the context of core norms and values, and ultimately crowned with licensure and admission to certified boards of practice. This identification falls within the organizational structure of the community of practice, not the façade of an organization or, in this case, a formal health care provider structure. “While some negotiation of noncore items is possible, failure to accept those deemed essential
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can result in marginalization or actual exclusion” (Wenger, 1998; Cruess et al
2014).
It is the community that determines and oversees the standards of practice by which competence is determined. According to Mann et al (2011) learning is a social rather than an individual activity and much of it occurs at the unconscious level, resulting in the accumulation of tacit knowledge. “The learning is ‘situated’ in the community and the content is given authenticity because it is acquired within the same context in which it is applied” (Cruess et al, 2018; Lave, 1991).
Participation enables individuals to establish meaning through the transformation of abstract knowledge to a foundation of something personal and unique (Cruess et al, 2018).
Medicine as a profession can be characterized by the three essential elements of a community of practice: domain, community, and practice. Snyder and Wenger (2010) state that there must be a domain with clear boundaries creating common ground and common identity. Similarly, they posit that the presence of a community creates the social fabric within which learning occurs.
Medical specialties constitute strong communities of practice. Finally, according to Wenger (1998):
Practice refers to the specific knowledge and skills that the community shares and develops, consisting of a set of frameworks, ideas tools, information, styles, language, stories and documents that the community members share. . . in medicine practice consists of clinical care, educational practices, and research (Wenger, 1998).
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“The word practice encompasses a social environment in which both work and
learning take place” (Cruess et al 2018). The juxtaposition of these three elements
constitutes an ideal knowledge structure that assumes responsibility for
developing and sharing knowledge (Wenger, 1998). Cruess et al (2018)
summarize as follows:
The knowledge base consists of a mixture of explicit and tacit knowledge that is acquired by those wishing to join the community of practice. The community is responsible for the creation and maintenance of the knowledge base, which is constantly being revised, in part through the process of negotiation that takes place as new members achieve full participation. The dynamic interplay between teachers [key opinion leaders] and learners [practicing physicians] within the community has an impact on the relevance and the vitality of the knowledge base by renewing it as it is recreated by individual learners (Cruess et al, 2018). The self-image of physicians and the community in which they acquire knowledge and
practice medicine is a powerful milieu that transcends their employment or contractual engagement with any organization. Is the physician community of practice, therefore, subject to the same forces within organizations seeking to make changes in systems, policies, practices, or standards? Or are there countervailing forces at work?
This notion of the role of “communities of practice” in resistance to a paradigm shift
or to change more generally in the administration of medical practice is largely neglected in
the literature. Given the above backdrop, the profession of medicine at large is, indeed, a
community of practice. More to the point, however, the Board of Medical Examiners’
certification of specialties creates the operant communities of practice which individually
reach scientific and clinical consensus on new approaches to diagnosis, intervention, and
patient care. Each specialty has its own criteria for determining what can be embraced as
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legitimate practice in accordance with standards of behavior, decision making and
acceptable clinical outcomes, i.e., standards of care.
In the US context, there are State Boards of Medical Examiners that license the
practice of physicians state-by-state, and there is the American Board of Medical
Specialties. Both of these constitute communities of practice, as fall under the definitions of
Brown & Duguid (1991) and Cruess et al (2018). Moreover, the Specialties share many of
the characteristics of guilds as explored by Mudambi and Swift (2009). The contrasting
roles are noteworthy:
State medical boards are the agencies that license medical doctors, investigate complaints, discipline physicians who violate the medical practice act, and refer physicians for evaluation and rehabilitation when appropriate. The overriding mission of medical boards is to serve the public by protecting it from incompetent, unprofessional, and improperly trained physicians. Medical boards accomplish this by striving to ensure that only qualified physicians are licensed to practice medicine and that those physicians provide their patients with a high standard of care (Carlson & Thompson, 2005).
Similarly, but with substantial differences:
. . . by 2002, the core group of the 24 member boards of the American Board of Medical Specialties (ABMS) had a firm set of shared guidelines and requirements for board certification. The specialty boards were created in the first part of the 20th century as medical science was beginning to advance, and physicians were beginning to gain specialty knowledge. The primary reason for specialty boards was to identify the boundaries and the content areas that defined specific specialties. It was a time, shortly after the Flexner report, when American medicine was beginning to try to distinguish itself from the proprietary physicians trained by apprenticeship, many of whom had little science base and were often considered “snake oil salesmen” (Cassel & Holmboe, 2008).
These communities of practice in medicine are not the stuff of casual, social
organization. Rather they were organized deliberately, often as a result of clinical
mishaps on the negative inspiration side, or through the relentless improvements in Page 173 | 477
technology on the positive side. The boards ultimately set rigorous standards of care and
of practice and have responsibility for policing members of these communities. These
communities of practice, therefore, are conservative and will resist change because
consensus must be built formally and informally within the community typically as a
result of cumulative experience and the consolidation and analysis of data. In the absence
of promulgating standards of practice the price of error is extremely high in terms of lives at risk and the reputation of the community.
This literature review on resistance to change, therefore, is obliged to study communities of practice. “In summary, a combination of knowledge and practice is required to maintain board certification in the United States. The boards are independent
entities of peer review, without legal or regulatory status but with significant impact in
the marketplace. Given the legitimate public interest in rigorous physician qualifications,
it will be ideal if the profession itself can provide trusted and meaningful oversight”
(Cassel & Holmboe, 2008).
If the pace of the adoption of medical innovation moves more slowly than say
earlier in history, can the resistance of communities of practice be implicated? Casadevall
(2018) explores the question of slowdown. He observes:
The pace of biomedical innovation is important because it determines the rate of progress in medicine and allied disciplines. A review of the history of medical advances reveals that the three decades from 1950 to 1980 were a particularly innovative time. Subsequent decades have seen fewer seminal advances, despite continued improvements in many biomedical technologies. Although the biomedical sciences continue to be innovative, the question posed in this essay is whether the rate of innovation has slowed relative to the available knowledge base. The pace of innovation varies tremendously depending on the specific field considered. Overall, the pace of innovation may be slower than in the past, especially when measured against the biomedical knowledge base available today versus that available then (Casadevall, 2018). Page 174 | 477
He then identifies ten factors that might bear responsibility. None are suggestive
that the role of communities of practice are implicated. The factors cited are:
reduced investment in science and technology; pharmaceutical industry priorities;
regulatory obstacles; exhaustion of low-hanging fruit; bad science; research priorities; academic priorities; decline of clinical research; distracting leads; and perverse academic incentives (Casadevall, 2018). While a coherent case can be made and documented for each putative cause, the organizational and professional practice elements are not taken into account.
In a recent article, Barry et al (2019) explore if the broker role of clinician- scientists in linking research and practice is a function in the pace of technological diffusion. The authors find that while the potential role is strong, more attention should be paid to these professionals learning multidimensional skills and managerial insights for supporting their role in translational as well as adaptive research. Do such agents function within the milieu of communities of practice?
This observation is further suggestive that progress requires a prime-
mover or advocate for technological adoption. While there are key opinion leaders
in every specialty, they can influence the community of practice but not compel
the movement towards new standards. What are the underlying causes of such
reticence? Dubois et al (2013), take a unique approach in answering this question:
Enthusiasm about comparative effectiveness research (CER) and funding to perform it will only benefit patients if they and their providers incorporate the resulting evidence into routine practice. In 2001, the Institute of Medicine [Institute of Medicine, 2001] issued a highly cited report on the ‘quality chasm’ between scientific evidence and routine medical practice. The Institute of Medicine noted that it takes ‘an average
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of 17 years for new knowledge generated by randomized controlled trials to be incorporated into practice, and even then application is highly uneven.’ However, the 17-year delay does not always occur, and in some cases the opposite does: medical technologies are adopted in an absence of sufficient evidence of benefit and safety (Dubois et al, 2013).
Again, the notion of prime-mover or agent must be raised.
This exploration implies the question of the role of boundary spanning, a term that describes individuals within an innovation system who serve the role of linking the organization’s internal networks with external sources of information
(Tushman, 1977). The theory postulates that all systems have a transference across their boundaries that is facilitated by the boundary spanner. In the corporate setting, this can be a designated or self-appointed individual who carries respect as an opinion leader. As will be seen later in this Study 2, at institutions
Alpha, Beta and Gamma, the function of boundary spanning is described, although not in so many words. All three institutions specified that there are multiple individuals that play that function, especially in the migration of precision medicine across specialties, by way of example from oncology where it dominates, to other specialties such as cardiology where precision medicine is beginning to gain ground at these institutions. Do boundary spanners exist within communities of practice? No doubt they do but their role in the translation and advocacy of precision medicine is not yet documented and is an area for future research.
The emphasis is on communities of practice at a national or even international level because these are the dominant entities in the determination of a standard of practice. There can also be a local – intra-institutional – functioning of a community of
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practice. For example, at an academic health center, there are typically relatively large
aggregations of specialists in a department or a division of a department. Specialists in
these groups essentially form a community of practice, and sometimes an influential one
when the group or department has a reputation in the larger community for important
research and publication. In the case of Alpha, Beta and Gamma, it appears that the
boundary spanners within the large specialty departments are the change agents.
Boundary spanners are likely to emerge from academic departments and form the linkage
between a particular institution and the community at large, or vice versa. Essentially,
there is a two-way flow from the academic institutions to the community at large, and
from the community at large to the academy. At hospitals functioning in a non-academic
environment, i.e., community hospitals or clinics, a boundary spanner is less likely to
emerge and movement of a standard of practice is most likely to flow inward from the
community of practice at large.
Finally, there is the notion of the specialty community of practice having
influence over provider organizations. This is a question of agency in the function
of absorptive capacity, or “a firm’s ability to recognize the value of new
information, assimilate it, and apply it to commercial ends” (Cohen & Levinthal,
1989, 1990). In the precision medicine setting, “commercial” translates to clinical application. The copious literature on absorptive capacity addresses individual, group, firm, and national levels. The role of communities of practice specifically is not addressed but given that the antecedents are prior-based knowledge and communication their function is plausible if not self-evident. Alpha, Beta and
Gamma, it will be demonstrated in the interviews, each demonstrate the requisites
Page 177 | 477 for absorptive capacity, again without identifying their capacities or managerial approaches as such. In all three cases, the institutions invest in translational as well as clinical research, thus increasing their absorptive capacity.
Has the movement of Alpha, Beta and Gamma proceeded towards precision medicine because of reconciliation with and within communities of practice or despite it? Most likely, there is a bidirectional flow of credibility, persuasion, and policy formation. While this study does not probe the degree to which communities of practice function within Alpha, Beta and Gamma as compared to one another let alone health care providers at large, as will be seen the interviews do suggest a cohesiveness and ethos that might make these institutions exceptional in this regard. Further investigation of community of practice culture among health care providers in the face of clinical change or challenge is warranted.
Communities of practice, the case is being made herein, are often bulwarks of resistance. They can also, however, become advocates once a critical mass of knowledge, experience and certification of an approach is met. This role of Alpha, Beta, Gamma, and other leading institutions influencing the specialty communities of practice towards ultimately establishing standards of practice across medicine and its specialties is a plausible hypothesis which should be tested in future research. Furthermore, as will be demonstrated in the interviews the resident communities of practice are the internal factors in precision medicine enablement at those institutions, and by way of their progress influence other internal specialties and provider communities at large.
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Do Communities of Practice Function Similarly to Organizations in Matters of Change?
The remainder of this literature review surveys general organizational theory on resistance to change and health care organizational theory addressing resistance to change. The literature streams define and characterize change, organizations, resistance to change, and the participants who live in the environment of change. While the literature in places describes change in the face of organized labor or professional groups, such as engineers or accountants, the literature on change and resistance to change does not emphasize the existence or power relationships that exist in communities of practice.
In the case of medical practice and the delivery of health care within the context of an organization this is an unfortunate omission.
The literature studied herein on resistance to change in health care does address factors that influence individual practitioners, but it does not consider the impact of communities of practice, especially the characterization of medicine and its specialties as communities of practice. Precision medicine represents resistance to changes in practice as will be demonstrated in the interviews at the three institutions. More importantly, data extracted from the interviews demonstrates that the nature of resistance by medical practitioners is not aptly described in the existing corpus of literature. This study will demonstrate that physicians are acting or resisting under the primacy of their community of practice and that conventional remedies to resistance to change are not wholly applicable owing to the force of such communities.
A community of practice in medicine will respond to evidence suggesting that approaches to prevention, diagnosis, procedure, or therapeutic intervention should be changed, but the individual physician is reacting within the framework of the community
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of practice – the community which establishes and oversees standards of practice. When
the impetus of change is a straightforward new development or innovation, the
community can respond, sometimes with alacrity. On the other hand, when the change
affects fundamental clinical decision making, practice patterns, the patient care journey,
ways of measuring outcomes or means of rewarding services, the community of practice responds more thoughtfully but slowly. In other words, the changes associated with the paradigm shift of precision medicine are subject to assessment, validation, and consent by the community of practice, thus the management of resistance must be through a paradigm of similar force directed at the collective.
The exploration of the literature of change provides the basis on which this study
can determine the congruity or incongruity with prevailing change theory of professional
behavior when confronted with a Kuhnian paradigm shift. That assessment and the
associated conclusions occur at the end of the study following the analysis of the
interview data.
The organizational behavior literature that is focused on resistance to change is
reviewed below in two categories: general organizational theory on resistance to change,
and health care organizational theory addressing resistance to change. The latter shares
much with the former, but the health care literature also offers frameworks, narratives
and explorations that highlight the unique elements of resistance in health care settings
that are useful in designing and interrogating the three sets of institutional interviews.
Comparing and contrasting the two categories – general organizational theory on resistance to change and health care organizational theory – provide additional useful insights for designing future studies in the area of physician attitudes.
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General Organizational Theory on Resistance to Change
There are several streams of literature in general organizational theory that address resistance to change that are captured in published literature reviews. The five that are most relevant are:
1. Typology of evolutionary and strategic change (Pardo del Val and Fuentes,
2003)
2. The relationship of research and practice (Erwin & Garman, 2010);
3. Positioning attitudes towards change (Bouckenooghe, 2010);
4. Reactions to organizational change (Oreg et al, 2011);
5. Changing nature of change resistance over time (Jones & Van de Ven, 2016).
Each stream and review will be explored in turn for its relevance to this investigation.
The first literature stream concerns the typology of evolutionary and strategic change. Change in an organization can be observed empirically as regards to structure of an organization, the scope and implementation of change, or status of change over time
(Van de Ven & Poole, 1995) in response to modification in thought processes, tactical shifts or operational modification (Schalk et al, 1998). The need for change is driven either by the need to adapt to a changing environment (Barr et al. 1992; Child & Smith,
1987; Leana & Barry, 2000) or improve performance (Boeker, 1997; Keck & Tushman,
1993) as documented by numerous papers early in the change literature. Of these factors, the principal typology for purposes of this study is scope and implementation of change because the fullness of adoption of precision medicine represents the paradigm shift previously argued in Study 1. This focus is aligned with the Five Levels described in the
PMC Landscape Study described above which is monitoring progress along a defined
Page 181 | 477 continuum starting with fundamental changes ranging to fully integrated change, and points in between.
This first stream of literature is congruent with the paradigm shift theme in that the typology describes first order changes that are evolutionary in some ways but incremental in others. These changes operate within existing frameworks and would correspond to PMC Landscape Study Levels One and Two. The second elements of the typology are the second order changes, i.e., strategic, transformational and revolutionary in which the fundamental framework is modified and would correspond to PMC Levels
Four and Five (Blumenthal & Haspeslagh, 1994; Goodstein & Burke, 1991; Greiner,
1972; Levy, 1986). The range of changes travels along a continuum seeking new competitive advantage or dynamic capabilities (Hutt et al, 1995).
Resistance to change, it follows, is the phenomenon that delays or obstructs the implementation of a new program. By extension, resistance to change seeks to maintain the status quo by virtue of inertia or passive aggressive positioning (Maurer, 1996;
Rumelt, 1995). Is resistance inherently negative? Not necessarily because change, when ill-conceived or sloppily considered can be detrimental to organizational objectives or the welfare of the participants (Waddel & Sohal, 1998). Following this stream of reasoning
Pardo del Val and Fuentes, 2003 posit the sources of resistance into five groups:
1. Sources of resistance and inertia in the formulation stage which typically
emanates from a distorted perception of the proposed program and hence its
underlying need. Operant factors include myopia (Barr et al, 1992) refusal to
acknowledge value of the new inputs (Rumelt, 1995); fixation on existing
methods even in the face of changing circumstances (Rumelt, 1995; Zeffane,
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1996); failure to comprehend the underlying assumptions (Starbuck et al,
1978); communication discontinuities or organizational silence leading to
misinterpretation (Hutt et al, 1995; Morrison & Milliken, 2000).
2. Low motivation for change driven by perception of costs and how they will be
accounted, contrasted with experience with past failures, or reconciled with
inconsistent expectations or rewards for the involved employees (Rumelt,
1995; Waddell; and Sohal, 1998).
3. All the above can be further driven by management’s lack of creativity in
assessing the overall situation, fatalism for achieving success or lack of a clear
commitment (Rumelt, 1995; Waddell; and Sohal, 1998).
4. Sources of resistance and inertia in the implementation stage. Once
management undertakes implementation, additional resistance groups can
emerge. The first of these raise political or cultural deadlocks within facets or
among working groups in the organization. The second set of objections is
based on disagreement regarding the nature of the problem or most effective
alternate solutions. Finally, there are concerns, not necessarily articulated,
regarding re-alignment of working groups and consequent interruption of
group values, loyalties, and social dynamics (Klein & Sorra, 1996; Schalk et
al, 1998; Beer & Eisenstat, 1996; Rumelt, 1995; Kruger, 1996; Lawrence,
1954).
5. Resistances with different characteristics. These include leadership inaction
driven by conflict avoidance or loyalty to the status quo; established work-
flow and related systems; ordering and prioritizing the affected work groups; a
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gap in capabilities; and, cynicism regarding the impact or results (Beer &
Eistenstat, 1996; Burdett, 1999) Maurer, 1996; Rumelt, 1995; Reichers,
1997).
The above five dimensions from the typology of evolutionary and strategic change
provide a useful lens when evaluating data from the interviews from the three institutions.
The second literature stream in general organizational behavior concerns the
relationship of research and practice. Erwin & Garman (2009) contribute a second valuable analysis of a literature stream with their review paper that studies research that identifies findings for providing research-based guidance to organizational change agents and managers in addressing individual resistance to organizational change initiatives.
Given the role of the individual physician practitioner in the acceptance and implementation of precision medicine, the survey elucidates key issues.
The findings offer practical guidance for understanding and managing resistance to change as might be applied to medical practice. The body of literature examined was concerned with the cognitive, affective and behavioral dimensions of individual resistance and how it is influenced by: individual predispositions towards openness and resistance to change; individual considerations of threats and benefits of change; communication, understanding, participation, trust in management, management styles; and, the nature of relationships with the change agents. The authors also present a framework for linking organizational change research findings to specific recommendations for change agents (Erwin & Garman, 2009).
Isern & Pung (2007) conducted a survey of 1,536 executives involved in change initiatives and learned that only 38 percent were considered initially successful with 30
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percent contributing to sustained improvement. There are other studies which corroborate
these findings (Prochaska et al, 2001; Bovey & Hede, 2001a, b). A major research
framework for examination of resistance to change stems from Lewin and Gold’s (1999)
unfreezing, moving, and freezing model of organizational change and analysis of
systemic factors (Damanpour, 1991; Burke & Litwin, 1992). These works also cited the
emerging attention to individual behaviors needs, values and motivation in understanding
success of change efforts. Given the nature of physician education and professional
development, and the context of standards of practice under which physicians operate,
individual behavioral factors are paramount in analyzing resistance to precision medicine.
Consistent with Study 2’s goals of elucidating the content of moves towards precision medicine implementation, “the what,” and the context of factors, “the how,”
Armenakis and Bedain (1999) illuminated how organizational change is interpreted and
responded to by organization participants. They reviewed stage-models of organizational
change such as Judson’s (1991) five phases of organizational change and Kotter’s (1995)
eight steps for effective change, as well as Isabella’s (1990) four-stage model that
includes: anticipation of change, conformation as implications of change are understood,
culmination in which results of change are assimilated and aftermath when change is
evaluated. Jaffe et al (1994) posit four reactions: denial that change will be implemented, resistance to implementation, experimentation with new behaviors and commitment to change.
Armenakis & Bedain (1999) further elaborate that the definitions of resistance can further represent any unfavorable reaction, a desire to use resistance as a means of refining proposed change, improve decision making promoting organizational learning,
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or resisting for the purpose of challenging implicit ethical assumptions in proposed
change – factors evident in the resistance to precision medicine.
Their overall observations address numerous relevant points for this study. In
reviewing the literature, Armenakis & Bedain (1999) maintain that resistance to
organizational change can be passive or overt. Resistance can be multi-dimensional with behavioral (response to change), cognitive (thoughts about change) or affective (feelings about change) dimensions. Piderit (2000) suggests that individuals often operate in all
three dimensions, sometimes simultaneously. Armenakis and Bedain (1999) also
explored individual personality variables in response to change such as predisposition to
resist or innate resilience to accept or cope with change. These personality factors include
preference for routines, negative reactions to announcements to change, short-term focus
or inclination to dogmatism.
Armenakis & Bedain (1999) also report that there are essentially two-working
dispositions among employees: self-concept and risk-tolerance. The former refers to a
sense of an internal locus of control, positive affectivity, self-esteem, and self-efficacy
whereas the latter refers to openness to experience, lower risk-aversion, and high tolerance for ambiguity (Judge et al, 1999). Bovey & Hede (2001) also observed adaptive
defense mechanisms that promoted acceptance (humor, as an example) or maladaptive
defense mechanisms that supported resistance, (denial, dissociation, isolation of affect,
projection and acting out). They further observed that individuals with a tendency to
blame others, to be inert and passive, conflict avoidance, and unwillingness to control
their own destinies or expand their notion of personal destiny, were also resistant to
change.
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These personality characteristics can be probed in future in-depth studies of
physician resistance to precision medicine. To further develop a framework based on
Erwin & Garman’s (2010) review, there are other questions to explore:
1. What are the key concerns of individuals upon the announcement of change
that influence resistance? These include self-assessment of competence to
deliver on new responsibilities associated with change, as well as perception
of the organization’s and co-workers’ competencies. (Giangreco & Pecci,
2005; Oreg (2006); Chreim (2006).
2. What is the perception of personal benefits, risks, or threats?
3. How does the organization’s internal process itself influence resistance to
change? Operant factors are communication, understanding of the messages,
consistency of implementation with the perceived change initiative (Wanberg
& Banas, 2000).
4. How does engagement and participation in the change effort promote
participation or resistance? How are buy-in, assignment delineation, role in
approval or veto, feedback-loops managed (Giangrecco & Peccei 2005)?
5. How do change agent/employee relationships and management interaction
styles influence resistance to change? Operant factors are prevailing levels of
communication, trust and confidence, atmosphere of skepticism and cynicism,
leadership style at each organizational level (Oreg, 2006; Stanley et al, 2005;
van Dam et al, 2008).
The framework derived from Erwin & Garman (2010) has utility in this dissertation in describing the interplay of organizations and individual attitudes and behavior; this
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interplay was explored in the interviews with the three institutions. For future research,
the framework can be used to survey more deeply physician attitudes towards resistance
generally and for the implementation of precision medicine in particular.
The third literature stream in the realm of general organizational resistance to change is captured in the review positioning attitudes towards change (Bouckenooghe,
2010). This article reviews the literature on attitudes toward change published between
1993 and 2007. Bouckenooghe (2010). finds that there is a need for a more complete typology of attitudes toward change that also fully captures the essence of resistance. By means of content analysis he first examined the conceptual overlap between the eight attitude-related constructs described in the review and then explored the working definition of attitudes toward change. Second, the concept “attitudes toward change” was described through four major theoretical lenses: (a) nature of change, (b) level of change,
(c) positive–negative view on change, and (d) research perspective. This conceptual review, he concludes, not only summarizes the current state of research but also offers a more complete typology of attitudes toward change, and highlights directions for possible future inquiry.
Attitudes towards change. People acquire a wide range of experiences in response to change. The reactions can be described in a positive light by use of terms such as readiness or commitment to change, or negatively using resistance. “Attitude towards change” and the process of attitude formation, however, are more encompassing constructs and have been the subject of numerous studies (Lines (2005); Vakola et al,
2004; Yousef, 2000a, 2000b; Lau & Woodman, 1995). Furthermore, Elizur & Guttman
(1976) conceived attitudes as a tri-dimensional concept composed of cognitive (opinion
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regarding advantages and disadvantages), affective (set of feelings about the change) and
intentional/behavioral components (actions in the present or anticipated for or against
change). These constructs anticipate the refined conceptualization of Armenakis &
Bedain (1999) above.
Bouckenooghe’s (2010) review also claims that there is a paucity of theoretical
contributions on attitude-related concepts and that the literature that does exist is constrained to two constructs: readiness for change and resistance to change, thus necessitating a narrative review of the broader concept of attitudes. He points out that attitudes can encompass readiness for change, resistance to change, commitment towards change, openness for change, coping with change, acceptance of change, adjustment to change, and cynicism about organizational change.
The definitions of the concepts delineated by Bouckenooghe’s (2010) are derived from multiple, overlapping sources:
Readiness is conceived as “organizational members’ beliefs, attitudes and intentions regarding the extent to which changes are needed and the organization’s capacity to successfully make those changes” (Armenakis et al, 1993). There is a strong emphasis on the cognitive component of this definition referring to the necessity or urgency for change. Cunningham et al (2002) further conceptualize readiness for change as a psychological process characterized by two stages: pre-contemplative in which the need is acknowledged, and the contemplative stage where benefits and risks are weighed.
Resistance to change is defined widely in the literature. Some authors define resistance as any set of intentions and actions that retards implementation of change (del
Val & Fuentes, 2003). Others see it as a necessary step in the promotion of organizational
Page 189 | 477 learning (Msweli-Mbanga & Potwana, 2006). Some research focuses resistance towards specific change in the workplace dynamic, e.g., resentment-based resistance based on perceived fairness, which can vary in intensity (Folger & Skarlicki, 1999). There are also conceptualizations of resistance that range from apathy or indifference to aggressive resistance or destructive opposition. Passive and active resistance fall in between these poles (Coestee, 1999). The afore-cited conceptualization from Piderit (2000) that resistance can be multi-dimensional with behavioral (response to change), cognitive
(thoughts about change) or affective (feelings about change) dimensions synthesizes the following definitions:
Commitment to change is “a force that binds an individual to a course of action deemed necessary for the successful implementation of a change initiative . . . this mindset can reflects (a) a desire to provide support for the change based on a belief in its inherent benefits (affective commitment), (b) a recognition that there are costs associated with failure to provide support for the change (continuance of commitment to change), and (c) a sense of obligation to provide support for the change (normative commitment to change)” (Herscovitch & Meyer, 2002).
Openness to change is comprised of two parts: (a) a willingness to support change and (b) positive affect about the potential consequences of change, e.g., feeling that the changes will be beneficial in some way (Miller et al 1994). Coping with change, therefore, is a cognitive and intentional framework.
Cynicism about organizational change involves a negative or pessimistic view regarding the success of change efforts which typically is a result of previous failures. It may reflect a loss of confidence in the change leaders or proponents (Reichers et al, 1997;
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Wanous et al, 2004). It is a cognitive attitude representing a lack of belief in the positive
outcome of a change due to incompetence and is manifested in increased resistance,
lower job satisfaction, reduced commitment, and deterred citizenship behaviors (Ferres &
Connell, 2004).
These approaches to defining attitudes to change factor heavily in the
implementation of precision medicine because they are suggestive of individual
responses as much as organizational, thus addressing change at the institutional level as
well as the physician practice level and by extension the community of practice.
Accordingly, Bouckenooghe (2010) posits four theoretical lenses to approach the four constructs: (a) the nature of change, i.e., planned or episodic change versus emergent or continuous change (Porras & Silvers, 1991); (b) the level of change, i.e., individual level
or collective level (Aktouf, 1992; Poole & Van de Ven, 2004); (c) the positive versus
negative focus on change, i.e., the negative problem-solving view versus the positive potential view (Abrahamson, 2004a, 2004b); and, (d) the research method, i.e., variance
or process methods (Mohr, 1982). These lenses are useful when analyzing the interviews
conducted at Alpha, Beta and Gamma. Bouckenooghe (2010) also offers a framework for
the theoretical lenses and their indicators, another useful framework in planning and
analyzing the three sets of interviews as summarized in Table 13.
The fourth literature stream in general organization theory related to change is
reactions to organizational change as captured in a comprehensive literature review on
the field by Oreg et al (2011). The study aggregates quantitative empirical studies of
change recipients’ reactions to organizational change. The authors reviewed studies
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Table 13: The Four Theoretical Lenses and their Indicators
Nature of Change Level of Change Positive-Negative Research Method View on Change Type of change Conceptual level View of human Measurement focus 1. Bottom-up driven 1. Individual level function 1. Attitude toward emergent change 2. Collective level 1. Negative focus: change as an that has a draws attention to independent continuous and approaches that variable (i.e., evolutionary Level of analysis stress negative antecedent) character 1. Individual level aspects of 2. Attitude towards 2. Top-down driven 2. Collective level organizations, and change as a planned change, dependent variable ways of change that has an overcoming or (i.e., outcome) episodic and dealing with 3. Attitude toward evolutionary problems change as a character 2. Positive focus: mediator/moderator emphasizes the variable positive reasons for change and the Measurement type potential created by 1. Quantitative change approach 3. Positive and 2. Qualitative negative focus approach
Measurement perspective 1. Data acquired from change strategists 2. Data acquired from change agents 3. Data acquired from change recipients Source: Bouckenooghe (2010)
published between 1948 and 2007. Through an inductive review, the authors formulate a model of (a) explicit reactions to change, in which these reactions are conceptualized as tridimensional attitudes; (b) reaction antecedents that comprise pre-change antecedents
(namely, change recipient characteristics and internal context) and change antecedents
(namely, change process, perceived benefit/harm, and change content); and (c) change consequences, including work-related and personal consequences. Their approach
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extends the frameworks through which the institutions Alpha, Beta and Gamma
interviews can be analyzed.
The structure of Oreg et al (2011) follows the model depicted in Figure 15. They
first define the term reactions to change. In the article the term explicit reactions is used
interchangeably with reactions. They distinguish between explicit change-recipient
reactions to change, labeled as explicit reactions to organizational change and more
indirect change-recipient consequences, which they refer to as change consequences. The
authors employ Piderit’s (2000) tripartite definition of resistance to change, which
includes affective, cognitive, and behavioral components of the reactions to the change as
a means for organizing the concepts.
Figure 15 as a summary of findings deals with change recipients’ explicit
reactions to change. The antecedents to explicit reactions are appropriately
conceptualized as the reasons for the reactions rather than the reaction itself. These
involve variables that predict either change recipients’ explicit reactions or the indirect,
and often longer-term change consequences. Depicted in Figure 15 are the five primary
antecedent categories we identified in the Oreg et al (2011) review: (a) change recipient
characteristics, (b) internal context, (c) change process, (d) perceived benefit/harm, and
(e) change content.
Oreg et al (2011) also introduce the concept of pre-change antecedents. These are
conditions independent of the organizational change and which existed prior to the
introduction of the change. These are compared to change antecedents, which involve the change itself and the change recipients’ explicit reactions, for example, the change process, perceived benefit/harm, and change content. These change recipient
Page 193 | 477 characteristics include differences in individuals’ personality traits, coping styles, motivational needs, and demographics (Ashford, 1988; Cunningham et al, 2002; Judge et al, 1999).
Figure 15: Antecedents, explicit reactions and change consequences of organizational change. Source: Reproduced verbatim from Oreg et al (2011).
Figure 15 also takes personality traits into account. One trait that has been linked with reactions to change is locus of control (Rotter, 1966). An internal locus of control, e.g., an individual belief that they are responsible for their own fate – was positively correlated with positive reactions to organizational change For example, managers with an internal locus of control were less likely to report experiences of losing control over their jobs during an organizational acquisition (Fried et al, 1996).
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Coping styles are also an important depiction in Figure 15. Change recipients who
adopt a problem-focused coping style report greater readiness for the organizational
change, increased participation in the change process, and an overall greater contribution
to it (Cunningham et al, 2002). Use of maladaptive defense mechanisms, such as denial,
dissociation, and isolation yielded greater behavioral resistance to an organizational
change in comparison with the use of adaptive mechanisms, such as humor and
anticipation (Bovey & Hede, 2001).
Motivational needs also factor into Figure 15. Motivational needs are
antecedents of reactions to change. Higher order needs, such as achievement and growth drive change recipients towards engagement in continuous organizational improvement
(Coyle-Shapiro & Morrow, 2003), participation in organizational restructuring (Miller et al, 1994) and experiencing positive affective reactions to their job (Bhagat & Chassie,
1980). Change recipients high in personal initiative tended to evaluate the outcomes of an organizational change more positively (Hornung & Rousseau, 2007).
In Figure 15, there are five process categories: participation, communication and
information, interactional and procedural justice, principal support during the change, and
management change competence.
Participation refers to the degree to which change recipients were involved in
planning and implementing the change. Drawing on the literature, Oreg et al (2011) point
out that such participation creates a sense of agency, contribution, and control over the
change (Armenakis & Bedeian, 1999). As a rule, change recipients who experienced high
levels of participation tended to report higher readiness and acceptance of change,
appraised change as less stressful, and exhibited overall support for the change (Amiot et
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al, 2006; Coch & French, 1948). Participation during the change process was also linked
with the experience of positive emotions, a greater understanding of the meaning of
change, realizing possible gains associated with the change and greater involvement in
implementing behavioral changes (Bartunek et al, 1999; Bartunek et al, 2006).
The amount and quality of change information provided to change recipients is
also a variable in Figure 15. Additional information and realistic, supportive, and
effective communication during change, was associated with several positive reactions,
such as greater change acceptance and support for the change (Axtell et al, 2002;
Gaertner, 1989). Alternatively, lack of communication during the change can lead to ambiguity – a key source of change recipients’ difficulties during change implementation
(Schweiger & DeNisi, 1991).
Principal support during change. The principals who have the most influence
over organizational change are change agents and opinion leaders. This is especially key
to an assessment of precision medicine adoption whereby physicians will
characteristically look to respected scholars and practitioners. Such support is distinct
from a general supportive atmosphere and refers to specific support that is provided as
part of the change implementation. In one study reviewed by Oreg et al (2011), principal support during change was associated with higher readiness to change and lower perceived negative effects of the change (Logan & Ganster, 2007).
Perceived benefit/harm from the change. A key determinant of whether change
recipients will accept or resist change is the extent to which the change is perceived as
personally beneficial or harmful (see Figure 15). Anticipated benefit and harm constitute
Page 196 | 477 straightforward and sensible reasons change recipients may have for supporting or resisting a particular change (Dent & Goldberg, 1999; Nord & Jermier, 1994). There are various variables that apply to this category, including:
1. Anticipation of negative or positive outcomes – change recipients’ reactions to
changes that entail negative outcomes, such as downsizing, a greater
workload, increased job complexity, or loss of job control. In these cases,
change recipients tended to experience greater stress and psychological
withdrawal (Ashford, 1988; Axtell et al, 2002; Fried et al, 1996), were less
open to accept changes (Cunningham et al, 2002), and exhibited lower levels
of job satisfaction and involvement (Hall et al, 1978) and lower levels of
perceived person–job fit (Caldwell et al, 2004; Susskind et al, 1998),
following the change.
2. Job insecurity. Perceived job insecurity was associated with greater job
dissatisfaction, mental health complaints, job-induced tension, and emotional
exhaustion (Naswall et al, 2005; Paulsen et al, 2005). In the case of physicians
in precision medicine circumstances, this is likely analogous to concern about
a loss of status or autonomy in patient care.
3. Change Content. Beyond the way change is managed or the implications that
change was expected to have, the content of the change may also affect
change recipients’ reactions.
The right column in Figure 15 depicts change consequences. The various antecedents (e.g., change process, internal context), according to Oreg et al (2011) are
Page 197 | 477 causally linked to change recipient orientation toward the organization following the change in a variety of ways:
1. Work-Related Consequences. In the literature the most fragile issue post change is
organizational commitment (Cartwright & Cooper, 1993; Fedor et al, 2006)
Other vulnerabilities are attachment to the organization (Spreitzer & Mishra,
2002), organizational identification (Johnson et al, 1996), job satisfaction (Amiot
et al, 2006; Axtell et al, 2002), turnover or intentions to leave the organization
(Coch & French, 1948; Fried et al, 1996), motivation (Pierce & Dunham, 1992),
organizational citizenship behavior (Shapiro & Kirkman, 1999), and morale
(Paterson & Cary, 2002).
2. Personal Consequences, specifically to change recipients’ psychological well-
being. These may include psychological withdrawal (Fried et al, 1996; Parsons et
al, 1991), psychological uncertainty (Rafferty & Griffin, 2006), exhaustion and
strain (Bordia et al, 2004; Paulsen et al, 2005) psychological withdrawal (Fried et
al, 1996), work-related irritation (Begley & Czajka,1993); perceived
psychological success or personal growth (Hall et al, 1978), emotional exhaustion
(Paulsen et al, 2005), and perceived control and uncertainty (Bordia et al, 2004;
Rafferty & Griffin, 2006).
These observations echo physician attitudes to change when they are unsheltered from support of their communities of practice.
As a rule, consistent with findings examining antecedents of the reactions to change, Oreg et al (2011) found that “as the conditions within which the change was applied were more favorable (e.g., supportive atmosphere, trustworthy management), as Page 198 | 477
the change process was more inclusive (e.g., high participation), and as change
recipients’ personalities were more resilient and change oriented, change recipients’
attitudes and behaviors toward the organization and toward their jobs, as well as their psychological well-being following the change, had improved. Thus, as would be expected, the impact the various antecedents had on the explicit reactions to change were comparable with their impact on the change consequences.” These are critical factors to consider in the interview process and analysis.
The fifth and final stream of general organizational theory on resistance to change concerns the changing nature of change resistance over time (Jones & Van de Ven,
2016). This research stream explores whether relationships between change resistance and its consequences and antecedents strengthen or weaken over time during an extended duration of organizational change. This is a significant question with respect to this manuscript because Study 1 asserts that given that precision medicine represents a paradigm shift, its absorption into science and clinical care will take place over decades or generations of medical practice. Moreover, Jones and Van de Ven (2016) conducted their analysis in 40 health care clinics undergoing a three-year period of significant organizational changes. The health care institutional research venue of the Jones & Van de Ven (2016) study serves as a convenient segue into the next section of this study’s literature review which is concerned with resistance to change in health care and in doing so is suggestive of a future stream of research that can emanate from this dissertation.
Jones and Van de Ven (2016) found that resistance to change over time had increasingly negative relationships with two important consequences: employees’ commitment to the organization and perceptions of organizational effectiveness. The
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authors surmise that “these relationships became stronger (rather than weaker) over time
suggesting festering effects of resistance to change.” They also found that over time
supportive leadership was increasingly impactful in reducing change resistance. A major
implication of this research for practice is that it is important for change agents to address employee resistance because, left unchecked, it can fester and increasingly inflict harm.
Also, engaging in supportive leader behaviors can be particularly useful in ameliorating resistance to change at later stages of a change initiative (Jones & Van de Ven, 2016).
In their discussion of the literature Jones & Van de Ven (2016) cite the observation that “change persists over the long term only when individuals alter their on- the-job behaviors in appropriate ways” (Choi, 2011). Furthermore, according to
Woodman & Dewett (2004) “it is not possible for organizations to change in meaningful ways unless employees change – people must think differently, they must believe differently, and they must behave differently.” Successful implementation of precision medicine, therefore, would rely heavily on leadership at the organizational level on the one hand, and within professional circles on the other. Effectiveness of implementation is a function of the extent of physician motivation and the staff that support them as the work of Armenakis & Harris (2009) suggests.
Jones & Van de Ven (2016) hasten to add that not all employees within a given
organization respond alike to the changes ongoing in their organization. While some
employees respond with enthusiasm others resist the changes (Caldwell et al, 2004;
Thompson & Van de Ven, 2000), while others are ambivalent (Piderit, 2000). Classically,
Dahl and Lindblom (1953) observed that response to change ranged from being heralded,
attacked, and sabotaged, or ignored. Recent work reveals individual’s experience and
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construct meaning about organizational change in a way that evolves as change unfolds
(Isabella, 1990; Sonenshein, 2010). Sometimes, change that starts out with a consensus of
support can experience a cascade of resistance as the impact of change is experienced
(Huy et al, 2014). Such a pathway may emerge in the practice of precision medicine as
clinical experience demonstrates utility or impact that differs from what has been
postulated in the early years, especially when standards of practice are formulated and promulgated by the community of practice.
The Jones & Van de Ven (2016) article captures that there is a limitation in the
understanding of change based on years of quantitative analysis. The Oreg et al (2011)
article discussed above, in their 60-year summary of quantitative studies on individual
change reactions, indicated that researchers probed the antecedents and consequences of
such change reactions in a static way. Current qualitative research, by contrast, suggests
that relationships between change reaction and its antecedents and consequences could
strengthen or weaken as changes unfold. “If these relationships are not static,” Jones and
Van de Ven (2016) assert, “then we may incorrectly assume, for instance, that certain
variables are influential throughout a change process when they actually play a role only
near the beginning or ending stages. We may also miss the true impact of change
resistance without recognizing that its influence (i.e., its relationships with outcomes) can
change over time, even though the amount of resistance may remain stable.”
“With the opportunity to add a temporal dimension to existing theory,” Jones &
Van de Ven (2016) asked, ‘Do the relationships between change resistance and its
outcomes strengthen or weaken over time as change persists?’ They also asked, ‘Do
Page 201 | 477 organizational antecedents become more or less influential on change resistance over time?’” Jones & Van de Ven (2016).
The Jones & Van de Ven (2016) findings suggest that a more dynamic conceptualization of organizational change in the context of major, long-term change initiatives is needed. This assertion is suggestive of the need to monitor acceptance of precision medicine into clinical practice over time. The current history of precision medicine is recent at best – the formal programs at Alpha, Beta and Gamma are scarcely a decade old, suggesting that the findings of this study will be tentative at best.
As will be discussed at the conclusion of this study, the research herein in combination with Jones & Van de Ven (2016), can in the future support theory by demonstrating that antecedents, e.g., supportive leadership and organization fairness, of attitudes toward change may play larger or smaller roles depending on duration and stage of change – a process that can be readily observed over the coming evolution of precision medicine. Future research will also have to test whether resistance to precision medicine is static or dynamic. Will precision medicine have a negative, festering effect on relationships within the medical specialties or between physicians and their provider organizations over time? These questions are beyond the scope of this study, but the groundwork for framing and testing those questions are established through this current inquiry.
Health Care Organizational Theory Addressing Resistance to Change
The literature focusing on resistance to change in health care is surprisingly limited, possibly because of the way that the industry is structured relative to other types of businesses. For example, physicians are the drivers of 80 percent of health care costs
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by virtue of their discretion to admit patients to hospitals, engage in interventional
procedures, order diagnostic procedures, write prescriptions, and other directives
(Norbeck, 2013; Fred 2016). While the employment relationship between physicians and hospitals is changing rapidly, about 30 percent of physicians are currently in private practice. Another 30 percent are in large group practices and about 40 percent are
hospital employees (Physician Advocacy Institute, 2019). The majority of physicians,
therefore, still work on the basis of “admitting privileges” with hospitals and although
subject to the rules and protocols of those hospitals, are not managed as employees or do
not necessarily collaborate with other physicians beyond referral patterns. This differs
dramatically from integrated clinical structures as found at the three institutions
interviewed for this dissertation.
Health care providers, therefore, are atypical organizations because the
relationship with their major agents differs from conventional commercial enterprises.
The organizational theory literature as it relates to change is formulated around different
structures. As such, the principles of organizational change as described in the first
section of this literature review should be applied to the issues of precision medicine with
caution and in light of several studies on health care resistance to change described
herein.
There are four articles on health care resistance to change that are relevant to the
questions surrounding the implementation of precision medicine in the existing health
care organizational structure:
1. Identifying sources of resistance to change in health care (Landaeta et al, 2008);
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2. Complexity, leadership, and management in health care organisations (Plesk &
Wilson, 2001);
3. Gaining and maintaining commitment to large-scale change in health care
organizations (Narine & Persaud, 2003);
4. Achieving and sustaining profound institutional change in health care: case study
using neo-institutional theory (Macfarlane et al, 2013).
The first article, Landaeta et al (2008), assert that the continuous introduction of new health care technologies and processes have accelerated the pace of change in the health care environment. Identification of the sources of resistance to change as guideposts for management, especially in the environment of precision medicine, are useful. Landaeta et al (2008) applied a phenomenology approach to evaluate 24 known sources of resistance to change in a unit of a hospital. The results suggested that there are sources of resistance to change that are specific only to the health care sector and by extension to precision medicine. There is general agreement that resistance to change is a factor that constrains health care organisations from making improvements and constraining costs (LeTourneau, 2004; Narine and Persaud, 2003). Appelbaum & Wohl
(2000) note that the inability of health care organisations to adapt to the changing demands of a highly competitive market is a barrier to their sustainability:
Traditionally, patients have not acted like conventional consumers who make deliberate purchasing decisions based on trading off products of service feature and economic impact. But this is changing. There is a shift towards the true health care consumer as being the central decision maker. Consumers are better informed and more assertive than ever with respect to their health care options. As consumers become better educated and bear more of the cost of health care decisions, they become increasingly demanding in terms of choice, access, quality of care, service, and price” (Appelbaum & Wohl, 2000).
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Health care’s pace of change will continue to accelerate in the face of new technologies and the precision medicine paradigm (Narine & Persaud, 2003). Resistance
to change in health care organisations is studied in a literature review by Appelbaum &
Wohl (2000) with additional proposed strategies to overcome resistance to change in
health care. The citations included Carroll & Edmonson (2002) who suggested that
leadership and organizational learning are constructs that can overcome resistance to
change in health care. Broadbent et al (2001) showed that change initiatives involving
decreasing or controlling costs influence physician decision making, a risky proposition
for influencing perception of the patient-physician relationship, a factor that can have a role in precision medicine adoption.
Sources of resistance to change can be organized in two phases: the stage at which
the change initiative is formulated and the stage at which the change initiative is
implemented. During the strategy formulation stage, Pardo del Val & Martinez (2003)
recognize sources of resistance to change (Table 14). In the strategy implementation
stage, Pardo Del Val & Martinez (2003) identify sources of resistance at the
implementation stage in Table 15. Tables 14 and 15 will serve as frameworks to inform the interview structures in this Study 2.
The second arena for addressing resistance to change in health care is borrowed from complexity theory and the relationship to leadership and management in health care organisations (Plesk & Kito, 1999; Plesk & Wilson, 2001). These articles stress complexity theory as an alternative approach for studying leadership. The methods of the papers are not directly relevant to this dissertation, but the conclusions and recommendations do relate to the core issues. Working backwards from the findings:
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Table 14: Sources of resistance to change in the strategy formulation stage
Source of Resistance Definition Myopia Participants inability to have a clear vision of the future Denial Refusal to accept any information that is not expected or desired Perpetuation of ideas Tendency to continue with present thought although situation has changed Implicit assumptions Conjectures that are not discussed due to their implicit character that can affect the way participants perceive reality Communication barriers Barriers that lead to information distortion Organizational silence Limitation on the information flow with individuals who do not express their thoughts, resulting in decisions that are made without all the necessary information Direct costs of change Price to be paid for what needs to be given up or invested in a change that is perceived as too high Cannibalization costs Costs resulting from a change that brings success to a product but at the same time brings losses to other products Cross subsidy comforts Comforts that results from the need for a change that is compensated through the high costs obtained without changes in another unit, so that there is no real motivation for change Past failures Failures from previous experiences that provide guidance and/or impediments to a change effort Different interests among employees and Lack of motivation exhibited by management employees who value change results less than managers value them Fast and complex environmental changes Changes that result from lack of time, stress, and several change initiatives being formulated at the same time that could overwhelm personnel and consequently do not allow a proper situation analysis Reactive mind-set Resignation that results from obstacles that are inevitable Inadequate strategic vision Lack of clear commitment of senior management to changes Source: Modified from Landaeta et al 2008 based on Pardo del Val & Martinez (2003)
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• Management thinking has viewed the organization as a machine and believes that
considering parts in isolation, specifying changes in detail, battling resistance to
change, and reducing variation will lead to better performance.
• In contrast, complexity thinking suggests that relationships between parts are more
important than the parts themselves, that minimum specifications yield more
creativity than detailed plans.
• Treating organisations as complex adaptive systems allows a new and more
productive management style to emerge in health care.
Table 15: Sources of resistance to change in the implementation stage
Source of resistance to change Definition Relation between change values and Gap between what is important for the organizational values individual and what is perceived important for the organization Departmental politics Change that can make entities lose power and some others gain power Incommensurable beliefs Strong and definitive disagreement among groups about the nature of the problem and its consequent alternative solutions Deep rooted values Importance of ethics and emotional loyalty Forgetfulness of the social dimension Changes in the psychological contract of changes Leadership inaction Lack of leadership or leader’s apprehension to change due to uncertainty Embedded routines Practices that become well-established over a long period of time Collective action problems Problems that result from a lack of coordination and teamwork Lack of necessary capabilities Lack of necessary capabilities Cynicism Pessimism that the change effort will not succeed Source: Modified from Landaeta et al 2008 based on Pardo del Val and Martinez (2003)
Complexity theory has immediate relevance to the antecedent conditions for precision medicine implementation. Plesk & Wilson, 2001 stipulate simple rules for the Page 207 | 477 design of 21st century health care systems that were anticipated in 2001 as the direction that is emerging for precision medicine. These rules are summarized in Table 16; their relevance is that they establish the ethos for the adoption of the precision medicine paradigm shift.
The third area explores commitment to change in health care and is best informed through the article “Gaining and maintaining commitment to large-scale change in health care organizations” (Narine & Persaud, 2003). The authors build the argument that health care administrators have sought to improve the quality of health care services by
Table 16: Simple rules for the design of the 21st century health care systems
Traditional approach New rule
Care is based primarily on visits Care is based on continuous healing relationships Professional autonomy drives variability Care is customized according to patients' needs Professionals control care and values Information is a record The patient is the source of control Decision making is based on training and Knowledge is shared and information flows freely experience Decision making is evidence based “Do no harm” is an individual responsibility Safety is a system property Secrecy is necessary Transparency is necessary The system reacts to needs Needs are anticipated Cost reduction is sought Waste is continually decreased Preference is given to individual professional roles Cooperation among clinicians is a priority over the system
Source: Institute of Medicine Committee on Quality of Health care in America, 2001
using organizational change as a lever. “Unfortunately,” they observe, “evaluations of organizational change efforts in areas such as total quality management (TQM), continuous quality improvement (CQI), and organizational restructuring have indicated that these change programmes have not fulfilled their promise in improving service delivery.” The explanations for these failures are elusive.
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The aim of the Narine & Persaud (2003) article was to provide insights into
practices that may be utilized to improve the chances of successful change management.
They propose that in order to effect change, implementers must first gain commitment to
the change through organizational readiness for change. Readiness is a function of first
deriving consensus and articulating dissatisfaction with the present structure and
operations, formulating through consensus an actionable vision of proposed changes,
driving participation in the change efforts, and developing a communication plan. The
authors observe that gaining commitment is necessary but not sufficient. Initial success of
a program is not a guarantee of success over time. Therefore, they conclude, “maintaining
commitment during the uncertainty associated with the transition period is imperative.
This can be done by successfully managing the transition using action steps such as
consolidating change using feedback mechanisms and making the change a permanent
part of the organization’s culture” (Narine & Persaud, 2003).
The action items proposed by Narine & Persaud (2003) are relevant to
formulating an interview strategy for the three institutions. They advocate consolidating
gains by using feedback mechanisms based on goal-setting theory which indicates that the best performance levels are achieved when specific and difficult (but not impossible) performance goals are set and specific feedback is provided on the attainment of these goals (Locke & Latham, 2002). Once the vision or end goal has been agreed upon, the health care organization and its members require ongoing feedback to determine goal achievement (Kotter, 1996).
In the case of a paradigm shift towards precision medicine, existing feedback mechanisms between the institutional laboratories and within the physician community
Page 209 | 477 are imperiled because acting on genetic inputs represents a radical departure from the status quo and results will be seen over longer periods of time. Thus, conscious efforts are required at re-establishing feedback systems early in the change process. In the case of precision medicine there must be an emphasis on establishing milestones along the path to full implementation and focus entirely on the end goals. Establishing these milestones are an opportunity for building physician engagement into the process and creating a sense of ownership (Schaffer & Thompson, 1996). Skeptics and cynics can be given the opportunity to frame the questions in ways that will satisfy their own doubt over time.
In the case of clinical care, the rewards would first be intangible, but it is beneficial to highlight tangible benefits as patient outcomes improve. Major clinical impacts will ordinarily be tied to the natural history of a disease, which can be of short or long duration. The collective sense of urgency is fragile if feedback and scientific discourse are not built into the implementation program (Hutton, 1997), but a process that communicates patient benefits and physician success can maintain the sense of urgency
(Lozon & MacGilchrist, 1999).
Momentum is imperiled by the ordinary course of administrative management and institutional politics. These stresses on the system must be observed and managed. In collaboration with the physician community, formal approaches to knowledge and information transfer are critical. Organizational initiatives should be structured and may include personal and group meetings with change recipients, articles in the organization’s public relations and information publications, and use of formal reward and recognition programmes (Huq & Martin, 2000; Lozon & MacGilchrist, 1999). The informal
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mechanisms should create an atmosphere of excitement and engagement. Feedback
approaches should be targeted to different stakeholders and to sub-groups within a
stakeholder category. Ultimately the goal is to make precision medicine the model for
care. This will occur by bringing the generations of physicians in clinical practice closer
to the newer generations, especially as precision medicine is institutionalized in medical
and nursing education.
The dynamics suggested by Narine & Persaud (2003) are important litmus tests to
incorporate into interview structure, data capture and analysis. The three successful
institutions profiled will likely have captured the principles formally or informally.
The fourth article exploring resistance to change in health care focused on
achieving and sustaining profound institutional change in health care through a case study
using neo-institutional theory (Macfarlane et al, 2013). Institutional Theory was cited in
Study 1 when considering the incremental normal science of precision medicine. In that
context, the milieu of paradigm changes invited reconsideration of the framework of
relationships among the stakeholders. Mrak et al (2017) were cited because they
advocated transaction cost economics (TCE) drawn from Institutional Theory as a means
for identifying relationship patterns among the industry actors in precision medicine. In contrast, Macfarlane et al (2013) considered transformational change, and the challenges of sustaining such change long-term, through the lens of neo-institutional theory, as applied to a case study of an ambitious long-term change effort.
This Study 2 would not be complete without addressing the relationship of
Institutional Theory to resistance to change as it might relate to the precision medicine paradigm. Institutional Theory is based on the resilient aspects of social structure. It
Page 211 | 477 evaluates the processes by which structures, including schemes, rules, norms, and routines, become established as authoritative guidelines for social behavior (Scott, 2004).
Institutional Theory explains how these elements are created, diffused, adopted, and adapted over space and time; and how they fall into decline. Given the function of precision medicine within the clinical environment, Institutional Theory both relates
(because it considers dynamic properties) and frustrates (because it appears to rely on authority structures which do not exist in medicine and hospitals the same way as in other organizational settings).
Macfarlane et al (2013) looked specifically, starting in 2003, at a £15 million grant by a charity to support a four-year partnership between two acute hospital trusts, two primary care trusts, community groups, patient groups and the independent and voluntary sector in the context of a multi-ethnic, inner-city population with high turnover and multiple diverse health and social care needs. They sought to study change and resistance to change in these settings over time using neo-institutional theory as the lens.
Neo-institutional theory argues that institutions are formed and changed by interactions between field and firm. It accepts that organizations and context are mutually constituent, thus actions within either analytical sphere reflexively affect both spheres (Gray, 2008).
Here again, this is perhaps too broad a brush with which to paint an analysis of precision medicine.
Macfarlane et al (2013) pointed out that there are many versions of neo- institutional theory. They point out that the one proposed by DiMaggio & Powell (1983) and further developed in relation to health care by Scott et al (2000) has its roots in organizational sociology. They write: “Institutions, defined as social structures that have
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achieved a high degree of resilience, are influenced by three broad types of social forces
or ‘pillars’:
• regulative (laws and contracts which stipulate what must happen),
• normative (assumptions and expectations about what should happen), and
• cultural-cognitive (taken-for-granted scripts and mental models about what
generally does happen) (Scott et al, 2000).”
DiMaggio & Powell’s (1983) description of “pillars” bears some relationship to the antecedent conditions for precision medicine, but only in the most generic way and may assume too much formality in the provider dynamic. Each pillar offers a different rationale for legitimacy, by virtue of being (respectively) legally sanctioned, morally
(e.g., professionally) authorized, or culturally supported. The three pillars are analytically
separable, but at an empirical level they tend to be intertwined. Mirroring these three
pillars, institutional change may be attempted by three fundamental mechanisms:
• coercive (by altering regulative pillars, as in top-down restructuring);
• normative (by altering the expectations of what is right and reasonable); or
• mimetic (for example, when organisations seek to copy what they
consider to be a model of best practice) (DiMaggio & Powell, 1983).
Scott (2000) puts a finer point on this construct by observing that health care systems sometimes seek to achieve “profound institutional change,” which he defined as
follows:
it is multi-level (involves new roles for individuals and/or new organisational forms), discontinuous (not merely incremental), and characterized by new rules and governance mechanisms (both informal norms and formal regulatory systems), new logics (that direct, motivate and legitimate the behavior of actors in the field), new
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types of social actors (both individual and organisational), new meanings (associated with the attributes or the behavior of actors in the field or the effects associated with them), new relations among actors (especially exchange and power relations), modified population boundaries (the boundaries separating organisational populations, organisations, customary activities, and personnel blend and blur), and expanded, reduced or realigned field boundaries (Scott et al, 2000).
Scott et al (2000) further write that external forces for change can be categorized into two types of environments: material-resource (which includes demand-side factors such as demographics and supply-side factors such as physician availability, technologies and external grants) and institutional (comprising institutional logics, institutional actors and governance systems) (Scott et al, 2000).
Institutional logics are socially shared, deeply held assumptions and values that form a framework for reasoning, provide criteria for legitimacy, and help organize time and space (Friedland & Alford, 1991). Through the duality of structure and agency, the institutional actors function as both carriers and creators of institutional logics (Giddens,
1986). They participate in both the material-resource environment (as ‘consumers’ or
‘suppliers’ of health services) and in the institutional environment (possessing institutionally-defined identities, capacities, rights and responsibilities; and by making meaning from their perceptions and experiences) (Scott et al, 2000).
Institutional Theory and neo-institutional theory are considered retrospectively in the analysis of the interviews. These concepts are not a priori in the formulation of the investigative framework of this dissertation but will be considered in the closing discussion.
Having explored the resistance to change literature generally and in relation to health care systems, many of the concepts contribute to the formulation of overall
Page 214 | 477 interview frameworks, specific concepts and questions to explore, approaches to processing the interview data, and a model through which findings can now be discussed and conclusions drawn. There is now enough background to derive the research questions and the methodology for proceeding with the goals of Study 2.
Approach to Formation and Exploration of Research Questions
To recapitulate, Study 1 explored a description of the precision medicine paradigm and its role in the transformation of clinical care for the providers and business activity for the producers. Moreover, Study 1 established that the complexity of this new paradigm of care has encountered resistance on the pathway to becoming the standard of clinical practice, whether it be in primary care, infectious disease, or the diagnosis and treatment of non-communicable diseases, particularly neoplastic diseases.
Study 2 seeks to determine those organizational structure and behavioral conditions that are antecedent or foundational for the launch and delivery of a precision medicine program at a provider level. Moreover, in response to the climate of resistance,
Study 2 explores the challenge of transformational change in health care organizations and among health care professionals, particularly in the establishment of standards of practice and care at the Level Five institutions in the PMC Landscape Study described above. Study 2 also relates general resistance factors described in the literature to precision medicine and suggests how that resistance informs organizational theory through contrasting provider institution progress.
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Basis for Selection of the Institutions Alpha, Beta and Gamma
One of the inherent challenges to this research is that the sample of provider
institutions that have developed and delivered comprehensive, integrated precision
medicine programs is severely limited as detailed above in the summary of the ongoing
PMC Landscape Study. As described previously, Alpha, Beta and Gamma are likely
among the principal four institutions that meet the Level Five criteria in the PMC
Landscape Study methodology and survey results. Alpha, Beta and Gamma have well
developed goals of precision medicine practice and harmonization of their business
model with pharmaceutical and diagnostic producers and the payers directly affiliated
with their own system.
These three provider organizations have also established the infrastructure for
precision medicine such as biorepositories, developed and integrated electronic medical
histories, a dedicated clinical and administrative staff committed to the adoption of
precision medicine, and internal education and promotion. The interviews also explore
the institutions’ historical perspective on how their precision medicine programs evolved,
where and why resistance was encountered, and how best practices are emerging within
their programs.
Patient Populations. Alpha and Beta serve very stable and compliant populations
that are essentially drawn from specific regional geographies. Their largely local patient populations have obtained care at these institutions or their predecessors over generations
and the institutions have captured in-depth family and individual health records, as well
as a collection of biorepository and pathology specimens.
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By contrast, Gamma, although it has a loyal population of patients from its immediate region for lifetime routine care and disease intervention, it also draws clients from throughout the United States and internationally for special procedures. Gamma also operates major hospitals in other states. During the earlier years of Gamma’s history, its population was stable and derived from primarily agrarian Northern European immigrants, but over the last two to three generations the population of the region has become highly diverse. Diversity especially characterizes Gamma’s out of state venues.
Broadly speaking, the gene-pool differences of Alpha and Beta compared to
Gamma are noteworthy but probably do not bear relevance to the processes of contemporary precision medicine, although it is worthwhile painting population characteristics with a broad brush given the importance of patient-centricity in the precision medicine enterprise, i.e., the importance of the patient-physician relationship, a central ethos of all three institutions in this study.
Alpha has served a well-informed clientele that is somewhat genetically homogeneous, non-migratory, and community-oriented for the purposes of gathering health history and biological specimens. Beta is the most recently formed institution of the three in the study, but it has a long heritage and one of the earliest institutional commitments to precision medicine.
Research Questions, Methodology and Data Sources for Study 2
Study 2 seeks to determine those organizational conditions that are antecedent or foundational for the launch and delivery of a precision medicine program at a health care provider level. Most of the existing literature on precision medicine addresses activities
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either at a health systems level or at a national policy level. Implementation at the level of
the health care provider and the associated organizational and professional behaviors are not addressed in the current body of literature in an integrated fashion.
In response to the climate of resistance described in Study 1 and the literature review of Study 2, the balance of this dissertation explores the challenge of transformational change in health care organizations and among health care professionals as a community of practice, particularly in the establishment of standards of practice and care at the three of the four Level Five institutions described previously in the PMC
Landscape Study. Study 2 also connects general organizational resistance factors
described in the literature to the resistance faced by precision medicine through the lens
of community of practice. In so doing, Study 2 demonstrates that the definition and
nature of change in the domain of precision medicine constitutes a new category of
change and an associated theory of resistance in the face of an evolving paradigm shift,
i.e., a shift still in search of a Kuhnian normal science, or in this arena, normal medicine.
The following conjecture, articulated by this author, establishes the context for the
inquiry of Study 2: Precision medicine is in a state of readiness for adoption, as
demonstrated in the data of Study 1, and by the fully integrated implementation at three
leading health providers in the US as described in Study 2. The basis for progress at these
institutions in contrast to resistance at the vast majority of health care providers is
revealed in the organizational commitment and dynamics of these few providers. They have evolved comprehensive diagnostic capability and delivery programs, built professional and managerial consensus and, developed direction towards a new standard
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of practice and touchstones for quality care. The communities of practice residing within
all three institutions are engaged with the process and drive implementation.
There are, therefore, three research questions for Study 2 that flow from the
confluence of issues imbedded in the above conjecture. They are:
Research Question One: Foundational concerns -- What are the antecedent conditions
for precision medicine to be incorporated into strategies for care delivery and
guidelines for professional practice?
Research Question Two: Provider readiness – How is precision medicine positioned
operationally to be incorporated into patient care based on cultures and systems
established at exemplary institutions?
Research Question 3: Change dynamics – What are the implications of the
pace of adoption of the precision medicine paradigm at the exemplary institutions
for the field of organization theory, in particular, its subfield of resistance to
change?
Methodology
The approach taken in Study 2 is qualitative, interview-driven investigation, within the Grounded Theory framework. In preparation for the Study 2 research, the author explored during a one-year period the relevant scientific, clinical, and
organizational theory literature, attended several precision medicine conferences, and had
discussions or meetings with thought leaders in precision medicine and health care
organizational theory. The expectation was that testable hypotheses would emerge. The
preparatory research yielded the opposite. Inconclusive and inconsistent inputs from providers indicated that Grounded Theory would be the optimal research framework. It
Page 219 | 477 offers a superior investigative framework, as opposed to a hypothetico-deductive approach, when asking fundamental questions.
Conclusions from a Grounded Theory approach are derived inductively based on questions addressed through a collection of qualitative interviews formulated to find thought patterns among the interviewees through language analysis and coding (Glaser &
Strauss, 1967; Martin & Turner, 1986; Strauss & Corbin, 1990). Grounded Theory is especially well suited for exploration of a new field of investigation, and in this instance, one characterized by a historic paradigm shift and amorphous approaches to implementation of new science.
Furthermore, Grounded Theory, according to Glaser & Strauss (1967), is a method well suited to enhancing knowledge of change and associated leadership, especially when exploring a paradigm shift. Grounded Theory uses qualitative research methods with the aim of generating theory, which is grounded in interview data, rather than testing existing theories or hypotheses. The value of the Grounded Theory approach in this research is that it incorporates the complexities of the institutions in the study without discarding, ignoring, or assuming away relevant variables.
The method herein, therefore, is anchored in semi-structured interviews which ultimately were rich with data. The goal, therefore, was to establish a basis for theory that provides a holistic understanding of the organizational antecedents necessary for the implementation of precision medicine. A preliminary interview strategy was developed around comments provided by prospective interviewees. Based on preliminary observations, an interview instrument was created and tested in trial interviews. Based on the trial interviews, the Grounded Theory objective was of grouping themes or codes into
Page 220 | 477 concepts, and then into categories as they took shape. These categories, this author conjectured, might suggest new organizational theory factors that illuminated resistance to change in circumstances like precision medicine, i.e., where there is resistance to change in a paradigm shift.
Three leading providers – Alpha, Beta and Gamma – with integrated precision medicine programs were targeted for inclusion in this research for two reasons.
Following intense canvassing of community opinion and the review of published reports on the outcomes of precision medicine this author identified these three potential candidate institutions. Subsequently, the preliminary results of a Landscape Study on
Precision Medicine conducted by the Personalized Medicine Coalition and released by
Health Advances (2019) implied in this author’s judgement that the three candidate institutions were among the national leaders. (NB: as disclosed above, this author is a member of the Steering Committee of the PMC Landscape Study, but the identity of the subject institutions was not revealed by the investigatory team conducting the research).
The precision medicine program heads or senior representatives at these institutions were approached in person during or shortly after precision medicine conferences. This author described the focus of this study and requested their participation in this research. In each case the program heads consented to participate either immediately or within a few business days. This author then followed-up with discussions regarding the most suitable professionals for interviews at each institution.
Ultimately, preparation led to 37 audio-recorded on-site semi-structured interviews with
50 scientists, clinicians, and administrators at the three institutions who are
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acknowledged as leaders or principal scientists and clinicians in the practice of precision
medicine.
At the request of two of the three participating institutions for anonymity, the
identity of the institutions and their staffs is shielded in this study – similar to the
provisions of the PMC Landscape Study. In addition, observations and quotations by the
staff are allowed for publication but are not to be attributed by name or institutional
affiliation. As stated previously, the institutions will be referred to herein as: Alpha, Beta
and Gamma. All three are major care providers which have these common characteristics:
-cross-functional care structures and collaborative physician cultures,
-employment relationships with physicians (rather than admitting privileges),
-stability and longevity of the physician and administrative base,
-established infrastructure and results for genomic and clinical research,
-significant contributions to the precision medicine literature,
-highly developed systems for ethics review,
-sustainable non-profit operations financed through care charges and donations,
-capacity for significant annual investment in precision medicine (in the aggregate
the three institutions invest over $100 million annually on precision
medicine implementation),
-comprehensive movement away from fee-for-service to value-based care,
-highly developed, long-standing Electronic Health Records systems (EHR),
-evidence based decision making challenged in weekly group care conferences,
-massive banks of integrated historic records and biobanking samples,
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-commitment to perform genetic sequencing across their patient populations,
- “captive” insurance functions covering most patients receiving care,
-major internal professional educational programs and patient outreach,
-long-standing, nurtured trust relationships with their patient populations.
To recapitulate, Alpha serves a significant portion of one US state, Beta the whole of another US state, and Gamma a regional population but with national and international outreach. In order to address the three research questions and derive theory on resistance to change, as previously stated, the author assembled a sample size of 37 interviews with
50 professionals from the three institutions.
With respect to sampling and the representative nature of studying three institutions under these circumstances, there is scientific validation. For example,
McKelvey & Andriani (2005) make a compelling case that characteristically the answers to research questions or the teaching of best practices is typically based on sampling drawn from a Gaussian distribution of organizations, but that this conventional approach can be misleading thus allowing for other designs for gathering and analyzing data. They maintain that in assessing strategy:
A non-Gaussian world demands statistical methods that take into account path-dependency, nonlinearities, emergent properties of systems and the dynamics of multiple punctuated equilibria. The assumption of independence which underlies the Gaussian world and the classical reductionist 'variance theory' approach [Mohr, 1982] leads to the wrong analytical tools and conclusions when dealing with connectionist dynamics [Kauffman, 1993; Holland, 1995] (McKelvey & Andriani, 2005).
Thus, exploration of the institutions performing precision medicine at the right tail of the distribution would yield the richest and most reliable insights.
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In the case of precision medicine as practiced at Alpha, Beta and Gamma, the
focus is on three statistical outliers skewed to the far right of the distribution of national experience in precision medicine, and they are representative early-adopters and full-
integrators as characterized in the PMC Landscape Study. In these circumstances, analysis based on Gaussian distribution of the universe of health care providers would be potentially misleading. The PMC Landscape Study, with n = 156 responding institutions out of 6000 provider organizations in the US, discovered this distribution among five pre- defined levels of precision medicine implementation:
Level One Providers: Individual physician adoption on a limited basis: 15 percent.
Level Two Providers: Individual or group adoption but with little to no support
from institutional leadership: 31 percent.
Level Three Providers: Inconsistent but strong use of precision medicine in one or
two areas: 32 percent.
Level Four Providers: Strong data collection with consistency for genomic as well
as clinical/economic outcomes data: 19 percent.
Level Five Providers: Expansive and integrated implementation: 3 percent.
Should this dissertation, therefore, expand the sample size in terms of institutions and interviewees? While it might perhaps seem more compelling to have a dozen or even a handful of similar institutions across the five levels of adoption described in the PMC
Landscape Study, there would be limited insights gained from all but the Level Five
Providers – for purposes of this study – although future investigation might explore the organizational dynamics at the other levels with particular attention to inertia and resistance. With respect to expanding the number of Level Five Providers in this study,
Page 224 | 477 the current census of integrated precision medicine providers is a severely limited universe, i.e., four institutions out of 156 providers responding to the survey of which three agreed to participate in this research. The institutional sample size of three was compensated by many in-depth interviews at each provider with clinicians, scientists and managers at the three institutions probing a comprehensive set of questions drawn from the review of the organizational theory literature on resistance to change and a systems analysis of the physician path and patient journey.
Analytic Framework for Interview Data
To extract observations from the interview data under the Grounded Theory methodology, the author used open coding for the categories that were represented in the abstract by the data. Open coding entails labeling and defining concepts, and developing categories based on the properties and dimensions. To determine the relationships between categories, a number of coding ‘‘families’’ (Glaser, 1978) were employed. The principal coding family is the ‘‘Six Cs’’ which considers the causes, consequences, contexts, contingencies, covariances, and conditions for each data category.
Theoretical coding using the Six C coding families prompted several questions of the data and categories to help clarify their relationship with one another. Those questions are as follows:
• C-1) What are the conditions or antecedents?
• C-2) Are the conditions a cause or a consequence of some other category?
• C-3) What are the intervening conditions between the causes and consequences?
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• C-4) Within what context does this category emerge? Context refers to the location
of events or incidents pertaining to a phenomenon (Strauss & Corbin, 1990).
• C-5) Is this category a contingency (having a bearing on another category)? In
other words, what is change in this category dependent upon? This refers usually to
unplanned change (Strauss & Corbin, 1990; Swanson, 1986).
• C-6) Is there covariance between this category and other categories? Covariance
occurs when one category changes with the changes in another category without a
causal connection (Strauss & Corbin, 1990).
‘‘Causes’’ reflect questions aimed at considering the reason or explanation for the occurrence of a given phenomenon. ‘‘Consequences’’ are the effects of the phenomenon.
In terms of the scientific approaches to research, Causes and Consequences reflect the relationship between dependent and independent variables. A contingency is, in effect, a moderating variable. An intervening condition is, in effect, an intervening variable.
Covariance between categories is equivalent to correlation. The context accounts for the setting and events imposing on the setting.
Qualitative data analysis was assisted by the Nonnumerical Unstructured Data:
Indexing, Searching and Theorizing (NUD*IST Vivo or NVivo), a computer software package designed by Qualitative Research and Solutions (Fraser, 1999). NVivo was used for the following interview data management and analytic procedures:
• Storage and categorizing of interview transcripts, memos, and other documents.
• Creation of categories through computer-assisted coding.
• Conducting searches relevant to analysis, in order to generate reports.
• Moving and linking data as higher order themes emerged.
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• Basic hierarchical models of codes.
The patterns generated in NVivo formed the basis for much of the final discussion in the
present study. While NVivo assisted with the storage and categorizing of data, the
analysis was conducted in accordance with Grounded Theory methodology. When NVivo
reached its analytic limits for purposes of this study, the author engaged in visual text
analysis and compilation of patterns and repeated observations by interviewees.
The 37 semi-structured interviews at the three institutions included 50
interviewees, were conducted on-site and in person by this author, audio recorded and
transcribed resulting in 569 pages of single-spaced text suitable for analysis. Under the
Grounded Theory methodology, once the interview data was collected, transcribed, and uploaded to the NVivo software, this author’s analysis followed these steps:
1. Coding text and theorizing: The search for the theory started with the first line of
the first interview that was coded. A segment of the text was used for line by line
coding with an eye for key phrases that were translated in named concepts.
Another segment of text was then taken, and the above-mentioned steps were
repeated. Essentially, the data was broken into conceptual components. The next
step sought more examples upon which theory could be based in search of a more
inclusive concept using a constant comparative method.
2. Memoing and theorizing: Memoing is the process by which the running notes of
each of the concepts that were being identified were captured and classified – in
this case for the construction of Propositions. Memoing is the intermediate step
between the coding and the first draft of the completed analysis.
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3. Integrating, refining, and writing up theories: Once coding categories emerged,
they were linked together as working concepts around a central category. The
constant comparative method was employed, along with negative case analysis
seeking instances of cases that neither confirmed nor contradicted the categories.
(Bernard & Ryan, 2010; Bazeley & Jackson, 2013).
The goal of using Grounded Theory with textual analysis is to identify patterns and ultimately Propositions from the interviews conducted at Alpha, Beta and Gamma.
Patterns were identified and articulated based on at least five mentions of an idea or observation made in each of the Themes/Nodes below. Propositions were formulated whenever a pattern emerged based on interview findings from at least two of the institutions. Assessment and grouping of the Propositions were expected to either support or invalidate the three Arguments of Study 2, as well as answer the Research Questions of Study 2. Support occurred across the board as will be seen.
Interview Themes and Questions
Exploration for the research questions was built around 21 interview themes derived from the matrices of precision medicine implementation appearing in Tables 19 through 21 in the following section on the Derivation of Themes and Nodes. Each theme was numbered and for purposes of coding in the NVivo software, themes were assigned
Node designations. Specifically, interviews sought non-confidential information on the following themes:
- Theme 1/Node 1: the leadership history of precision medicine at the institution
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- Theme 2/Node 2: clinical infrastructure requirements
- Theme 3/Node 3: data and bio-bank infrastructure for precision medicine
- Theme 4/Node 4: the degree of penetration of PM into integrated practice
in oncology and other fields of medicine
- Theme 5/Node 5: the degree of physician buy-in according to specialty
- Theme 6/ Node 6: the relevant clinical dynamics for precision medicine
to be incorporated into patient care
- Theme 7/Node 7: whether there are formal clinical protocols currently in
place or if protocols are a work-in-progress
- Theme 8/Node 8: the process for internal protocol development and
screening
- Theme 9/Node 9: human and financial resources required
- Theme 10/Node 10: costs associated with any given protocol
- Theme 11/Node 11: overall costs of administering a precision medicine
program
- Theme 12/Node 12: issues with payers for reimbursement
- Theme 13/Node 13: on-going scientific and clinical research objectives
- Theme 14/Node 14: monitoring and measurement of outcomes
- Theme 15/ Node 15: status of formation of precision medicine as the
standard of practice
-Theme 16/Node 16: education efforts and promulgation of the program
internally and to patients
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-Theme 17/Node 17: obstacles that were encountered in the development
of the precision medicine program
- Theme 18/Node 18: obstacles in the current development of the program
- Theme 19/Node 19: additional themes were framed based on patterns
or issues that arose during the interviews.
Two additional themes were added after interviews were underway based on the direction of the interviews to that point:
• Theme 20/Node 20: ethical considerations historically and currently
• Theme 21/Node 21: evolution and issues around process flow.
Table 17: Relationship of Coding Categories, Nodes, and Themes Explored in the Interviews Coding category Theme/ Theme explored Node # 1 - the leadership history of precision medicine at the institution 9 -human and financial resources required 13 - on-going scientific and clinical research C-1) What are the objectives conditions or antecedents? 16 - education efforts and promulgation of the program internally and to patients 20 - ethical considerations historically and currently 21 -evolution and issues around process flow 4 - the degree of penetration of PM into C-2) Is it a cause or a integrated practice in oncology and other consequence of some fields of medicine other category? 5 - the degree of physician buy-in Specifically, are the according to specialty derived conditions or 10 - costs associated with any given antecedents a cause or protocol consequence of the above 11 - overall costs of administering a factors? precision medicine program
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Table 17: Continued Coding category Theme/ Theme explored Node # C-3) What are the 2 - clinical infrastructure requirements intervening conditions 3 - data and bio-bank infrastructure for between the causes and precision medicine consequences? 17 -obstacles that were encountered in the Specifically, what is the development of the precision medicine relationship between the program causes and consequences of factors that drive precision medicine? C-4) Within what context 6 -the relevant clinical dynamics for does this category precision medicine to be incorporated emerge? Context refers to into patient care the location of events or 15 -status of formation of precision incidents pertaining to a medicine as the standard of practice phenomenon. Specifically, within what context do the conditions and antecedents emerge, i.e., what is the setting and dynamics of the precision medicine phenomenon? C-5) Is this category a 7 -whether there are formal clinical contingency (having a protocols currently in place or if bearing on another protocols are a work-in-progress category)? In other words, 8 -the process for internal protocol what is change in this development and screening category dependent upon? 12 -issues with payers for reimbursement Specifically, what factors 18 -obstacles in the current development of affect changes in the the program. antecedents or conditions – especially the pace – for the adoption of precision medicine? C-6) Is there covariance 14 - monitoring and measurement of between this category and outcomes other categories? Specifically, what is the strength of the correlation of precision medicine antecedents and conditions with other factors governing medical practice?
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Table 17 identifies the relationship of the Grounded Theory coding categories with the nodes and themes explored in the interviews.
Conducting the Interviews
The interviews were conducted on-site and in-person, and were audio recorded.
Table 18 identifies the professional functions of the 50 interviewees across Alpha, Beta and Gamma. Interviews were conducted in such a way as to allow this author to select themes and questions based on the functional role of the interviewees, i.e., all the themes were not explored with all the interviewees. This semi-structured approach permitted focused use of time with each interview but meant that the transcripts would have to be re-compiled according to themes, a process aided by NVivo. The interviews were
Table 18: Professional functions of the 50 interviewees at Institutions Alpha, Beta and Gamma. Numerous interviewees had multiple functions. Modifications in titles or functions were made to preserve anonymity. Managerial/Administrative System CEO Executive Vice President and Chief Scientific Officer Founder Precision Medicine Clinic Director, National Precision Health Director, Precision Genomics Chief of Precision Health Managing Director, Precision Genomics Associate Administrator Department of Laboratory Medicine and Pathology, Operations Administrator, Precision Medicine Operations Administrator, Clinical Genomics Director, Clinomics Program Operations Manager Clinomics Program Director Proteomics Program Director. Department of Clinical Genomics Manager, Project Management Director, Center for Precision Medicine Administrator, Center for Precision Medicine Scientific Professor of Oncological Sciences Co-Director Microbiome Program Microbiome Scientist
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Table 18: Continued Clinical Chair, Community Medicine Chief of Cardiology Director, Autism & Developmental Medicine Institute Chair of the Department of Medicine Specialties Director of the Division of General Internal Medicine Co-Director of Genomic Screening & Counseling Medical Oncologist and Director of Medical Oncology Director of Clinical Research Supervisor Genetic Counseling Hematology and Laboratory Medicine Consultant Technology, Testing and Director, Patient Sequencing Initiative (3) Biorepository Director Advanced Diagnostics Laboratory Development Principal Investigator, Screening Trial Director Biorepository Program Operations Manager, Biorepository Program Director Biomarker Discovery Program Operations Manager, Screening Trial Director, Medical Genome Research
Information Principle Data Science Analyst technology/bioinformatics Director Bioinformatics Director Omics Data Platform Chair, Bioinformatics, and IT Subcommittee Director Imaging Biomarker Program Chair, Translational Research Subcommittee Section Head, IT Pharmacogenomics Chair, Pharmacogenomics Subcommittee Chief Pharmacy Officer Health System Pharmacogenomics Pharmacist Specialist Clinical Implementation Pharmacogenomics Operations Manager Pharmacogenomics Founding Director Pharmacogenomics Program Director Pharmacogenomics Program Education Director Education Program Education Operations Manager & Conference Director Conference Director Ethics/patient experience Chief Patient Experience Officer Director, Bioethics Program
Page 233 | 477 immediately transcribed using a third-party transcription service, and then up-loaded into
NVivo. NVivo was used to categorize components of the interviews into master reports for each theme. Once the data was collated and reviewed, codes were grouped into concepts, and then into the “Six-C family” of Grounded Theory. Specifically, each theme was then curated for summary into Appendix F which is organized around the structure shown in Table 18. Table 18 is a thematic summarization of Appendix F. Appendix F does not identify the interviewees, but the author has preserved a key that can be used to establish a correspondence of observations to interviewees if needed for future research.
Driving Towards Interpretation and Conclusions
The process then turned to seeking and abstracting patterns and recurring themes with a focus on patterns that appeared to be supported by more than the opinion of one interviewee. The validity of the patterns was tested by comparing how precision medicine implementation is reported in the literature and is aligned with the preliminary results of the PMC Landscape Study. Thus, this approach differs from the traditional model of research that employs an existing theoretical framework and collects data to show how the theory does or does not apply to the phenomenon under study. As is discussed in the
Interview Results and Discussion sections that follow, conclusions are drawn from the patterns which enables kernels of new theory to emerge.
The Grounded Theory methodology allows Study 2 to draw conclusions for the following:1) establishment of antecedent conditions for implementation of precision medicine; 2) determination of requirements for acceleration of precision medicine; 3) postulation and interpretation of metrics for determination of impact of precision
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medicine; 4) approaches to the reconciliation of the different business models of the
stakeholders in precision medicine; 5) implications of the antecedents to precision
medicine to organizational theories of change; 6) implications for organizational theory
surrounding formulation of clinical standards; and, 7) implications for organizational theory related to resistance to change, especially to historic paradigm shifts. These findings are discussed in the section that follow the Derivation of Interview Themes and
Nodes.
Derivation of Interview Themes and Nodes
The derivation of the themes pursued in the interviews and the framing of the
discussions with the interviewees was based on informal meetings with other parties prior
to the interviews and on exploration of the literature for treatments of process flows and
program design in precision medicine. A matrix of macro-organizational issues to
overcome is presented in Table 19 which is based on an internal document developed for
a World Economic Forum project in which this author is involved on precision medicine
implementation in Rwanda. The matrix functions as a way of positioning major tasks
relative to the interrelationship of objectives and challenges.
Furthermore, based on Klein et al (2017), a framework was adopted and expanded
to inventory the issues at three stages of program development:
Stage One: Pre-implementation: research and synthesis of data foundation,
Stage Two: Developmental activities and organizational readiness,
Stage Three: Clinical implementation.
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Table 19: Precision Medicine Pilot Project Matrix
Objectives Data Sharing Reimbursement Regulatory Clinical Patient and Evidence and and policies practice public based Infrastructure integration engagement effectiveness Cultural readiness for precision medicine Breaking barriers to health data Restructuring clinical trials Diagnostic innovators dilemma Innovation in costing and reimbursement Source: World Economic Forum unpublished draft working paper
Each of these stages is represented in a three-part Table 20. The table identifies relevant categories for consideration at each stage. The author of this dissertation extends Klein et al (2017) by positing “Resistance or Chokepoints” (appearing in italics) that threaten the required actions in the categories. Together, these provided an inventory of issues for the interviews. The inventory in the Table 19 matrix, however, does not anticipate the issues that the Level Five institutions in the PMC Landscape Study are facing regarding potential for growth, sustainability of their programs, and integration of precision medicine with medical standards of practice. These issues are intimated in parts A, B and
C of Table 20. In other words, at maturity, should precision medicine programs be recognized as separate departments in an institution or should precision medicine be interwoven as a standard practice in medical care?
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Table 20, Part A: Process Flow for Development of a Precision Medicine Program and Clinical Management Strategy (Modified from Klein et al, 2017); italicized entries and resistance and chokepoints added by this author. Stage One: Pre-implementation: research and synthesis of data foundation Evidence Projects Financial Guidelines Facilities Stakeholders Committee Literature Review Funding FDA/EMA Lab Engagement Appoint review other projects equipment plan suitable institution Clinical members Hospital programs Reimburse- Pharmaco- IT Raising EHR ment genetics infrastructure awareness Develop Suggestions climate and Implementa- protocols History of and plans tion Communica- Consensus Rx and setbacks Consortium tion platform reporting Adjudica- treatments Cost Guidelines between tion of Resistance analysis clinical and Feedback ethical, assessment Pharmacogen- support loops legal, Feasibility omics services social of genetic Knowledge- implica- testing base tions
Drug labels
Key clinical areas Resistance or Chokepoints (added by this author) EHR Identifying Sources and Relevance Comprehen- History of Profess- adoption similar durability of and sive array of successful ional and structures financial adaptability genetic change commit- capacity and support of regulations testing management ment and cultures to instruments interest Integrated Relationship circumstances Project access to Curating with payers: Bioinfoma- management Prevailing Rx history suggestions captive Insight into tics base and depth SOP payers vs CPIC support culture Frank 3rd party Approach to assessment Determination Degree of consensus Depth and of attitudes Basis for of areas of silo structure building awareness assessing most relevant and of ELSI costs and clinical need cooperation Feedback issues benefits and exchange culture Capacity for genetic testing internally or outsourced
Interpreta- tion of genetic testing
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Table 20, Part B: Stage Two: Developmental activities and organizational readiness
Laboratory Bioinformatics Model and Systems Evidence for inking biomarkers Cooperative Distributive Point of care or preemptive and genes to drugs Systems Lab and consultation model
Population frequencies EHR selection (Cerner or Epic) Flow between departments
Guideline compatibility and Integration of HER with Movement of information reference genomic data Professionals involved: patient, Compile capability for Processing language physician, nurse practitioner, interpretation, e.g., diplotypes- geneticists, pharmacists phenotypes translation tables Reference linkages Assessment of resistance, Clinical Laboratory Database information storage barriers, and solutions Improvement Amendments (CLIA) protocols in place Omics-information consolidation Educational program delivery and interpretation internal Onsite/remote/out-sources Security and privacy measures Educational program delivery Array testing systems external Warnings fatigue Capture of incidental findings Outcomes measurement Assessment of utilization, Consent protocol related costs, and reimbursement Data monitoring
Resistance or Chokepoints (added by this author) Timing infrastructure for results Level of existing IT capacity and Institutional relationship with integration physicians, i.e., employee or Limited access to array of tests contracted privileges Attitudes to EHR Integration of other omics Turnaround times of testing Integration of genomics with Capacity for multiple array of EHR Treatment delays tests vs. single genes Data capacity Limited access to array of tests Ability to develop new tests or protocols Data security Systematic payer approaches
Integration of interpretation No universal lexicon Patient population diversity with clinical decisions and recommendations Early steps towards SOPs Ambiguous understanding of precision medicine
Lack of existing system for outcomes monitoring
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Table 20, Part C: Stage Three: Clinical implementation (italicized entries added by this author)
Stakeholders Patient Physician Program Evaluation Collaboration Communication Referrals Acceptance Ongoing Systematic Clinical expansion evidence- research Feedback and Selection Awareness based response Process assessment Internal Consent Creative improvements sharing of data Education engagement Process and Knowledge Delivery assessment information and awareness Accessibility improvements and utility Model Extramural Follow-up Outcomes modification scientific Decision assessment participation Locus of care support process Organizational impact of Engagement Feedback and Barrier implementation of primary response identification care physician Cost Representation Barrier effectiveness Diagnostic or management analysis and interventional response
Rare/genetic disease Resistance or Chokepoints (added by this author) Generational Awareness Professional Lack of clear Awareness and Extent of processing of linkages vision at top flexibility to clinical or information Accuracy of of institution make process scientific base of Personal or PM group change culture Media information, confidence approaches to e.g., Dr. regarding Resources Inability to Unwillingness transfer of Google integration of available to manage impact to outsource information PM with care sustain growth on overall or collaborate Insights of organizational with external Time primary care Insecurity Culture of systems established investment in or specialty about provider in programs explaining role physicians interpretation making Integration of of PM in care vis-à-vis process PM costs into Lack of Transparency therapeutic improvements overall care internal of consent strategy strategy protocols for process Insufficient sharing data feedback Inability to Weak patient mechanisms benefit from feedback for outcomes potential loops assessment savings associated with PM
Unproductive relationships with payers
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Table 21 is an addition to Klein et al (2017). It is created by this author and intends to identify the issues related to growth that can be captured in the interviews.
Table 21: Potentials for growth, sustainability, and integration as a standard of practice. Stakeholders Patient Physician Program Evaluation Collaboration Perceived Expectations Confidence Integration Comparative Perceived benefits over of precision that patients with general results with benefits of time by all care are benefitting care current SOPs clinical stakeholders remain positive research Experience Digestible and Reinforcement View towards with protocols actionable of impacts Tangible Access to long-run laboratory and measures for developmental integration of Outcomes data inputs outcome protocols PM with care assessment generally Acceptance by Accessibility peers Organizational to data responsiveness Acceptable to physician Confidence in changes in experiences data referral and patterns recommenda- Interpretation tions of data Patient retention
Neutral income impact Source: Conceptual extension of Klein et al, 2017; italicized text formulated by this author.
The themes and nodes for the interviews, therefore, are not random but are derived from a progressive representation of issues that are organized in the sequential fashion of the above tables.
Interviews: Summary of Findings and Derivation of Propositions
The interview process at institutions Alpha, Beta and Gamma were largely seamless. Although there were some minor differences in the points of view of the 50 interviewees, these differences were reflective of their organizational vantage points and responsibilities, not their fundamental views on precision medicine. Otherwise, there was Page 240 | 477 noteworthy but unexpected consistency among the interviewees across the three institutions. There may be several reasons for this consistency of viewpoints:
1. Alpha, Beta and Gamma are among the most elite institutions nationally in the
implementation and execution of fully integrated precision medicine
programs. All three institutions had significant insight in the operations of the
others’ precision medicine program and expressed respect for the other
leading programs. Two of the 50 interviewees had recently worked in similar
capacities at one of the other institutions.
2. Every interviewee made a personal and professional decision to commit
several or more years of their career to pioneering what many referred to as
“this paradigm shift” in the practice of medicine. Hence, the pool of
interviewees included consistently “true believers” in the potential of
precision medicine. The interview pool did not include skeptics, which was
not by design. The author expected to find a balance of committed and
dubious participants but was surprised by the uniformity of viewpoints. In
view of this experience, naysayers were most likely to be found among the
thousands of institutions that elected not to participate in the PMC Landscape
Study, as well as the scores of institutions that fell into Level One and Level
Two implementation.
3. All three institutions had fully committed financial and philosophical support
from the CEO level. Furthermore, the leadership qualities and palpable
admiration of the interviewees for the heads of their programs strongly
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suggested a cohesiveness to accomplishing the goals and objectives of the
programs. All three institutions shared a culture of collegiality.
4. Goals and objectives, and the strategy and tactics of the precision medicine
programs at Alpha, Beta and Gamma were developed and articulated at all
three institutions by active debate and consensus building, and actions derived
from these were consistently subject to regular analysis and the burden of
evidentiary performance, i.e., cultivation and consensus of the communities of
practice was acknowledged, managed and embraced.
5. Virtually all 50 practitioners framed their observations in the interviews
through either an ethical or patient-centric lens, or both. The integrated
clinical practice structure of all three institutions favored selection of
professionals with this orientation, and the same individuals self-selected to
practice medicine or administrative duties in such an environment.
Compensation profiles at this type of institution is less than at other hospital
and specialty providers, a suggestion that the professionals were oriented
towards promoting innovation in patient care over personal compensation.
Moreover, Alpha, Beta and Gamma are all located in locales with lower costs
of living and housing and are geographically isolated from major urban
centers. These may be additional factors in focusing professional attention on
the tasks of medical practice and relationships with patients.
Appendix F provides an exhaustive but nevertheless summary compendium derived from an NVivo analysis of interview observations across all six Coding categories and the 21 themes and nodes described in the methods section. Table 22 is
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abstracted and interpreted from Appendix F and summarizes the major patterns of
responses in the column headed as “Recurring Observations and Patterns.” The
Categories are synthesized in the fifth column to the far right and stated as Findings
(“F.”) in italics.
The Findings are based on raw word counts but primarily a visual text review.
They serve as identification of critical factors, antecedent conditions, and the best
organizational practices in the precision medicine programs at Alpha, Beta and Gamma
and are the basis of the discussion that follows in the next section. The Findings were
derived by observing the text for at least five interview statements made at two or more
institutions that suggested or supported the Findings. The Findings were articulated
herein either through direct transfer or incorporation of words or paraphrasing by the
intent of the statement. Numerous other ideas were repeated but not at the same
frequency and were not used as the basis for articulating a Finding. The number of
Findings could be increased if the criteria for repetition is reduced but that would be at
the price of robustness.
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Table 22: Relationship of Coding Categories, Nodes, and Themes Explored in the Interviews Coding Theme/ Theme explored Recurring observations and patterns Category syntheses and related category Node # Findings 1 What is the -Unique circumstances of formation. Category 1 asks what are the leadership -No institutional precedents. conditions antecedent to -Powerful institutional CEO’s commitment; top-down history of initially then bottoms-up on implementation. adoption of precision precision -Physicians are employees and not independent, medicine? The observations of C-1) What are medicine at the autonomous providers. the interviewees can be the conditions institution? -Standards of care and evidence-based assessment driven. synthesized into the following or antecedents? -Group-based procedure development objectively findings: assessed. -Commitment to sequencing broad swath of patient population. F1. The implementation of -Precision medicine seen as a long-term economic benefit precision medicine at an to the overall health care system. institutional provider is driven -Research focus is clinical not basic science. top down initially but developed -Genomics as a programmatic strategy. -Care must adapt to unique nature of our patient bottoms-up with significant, population. diversified human resources -Physicians in our community but outside the formal supported with reliable financial program are committed to learning and participating. commitment over the long-term. -Innovators must be willing to be misunderstood for a long period of time. -Champions for specialty application of precision F2. The practice culture must be medicine can be recruited but are more likely to emerge on flexible on the employment of their own. standards of care but ultimately -Widespread support came after the infrastructure and must make evidence-based systems were in place. assessments. Oncology is the -Value driven principles in formation. -Healthy debate is essential to progress starting point but must migrate -Planning is long-range but expectations are yearly. to other clinical verticals swiftly, -Shared vision on expansion from genomics and ideally with the emergence of a proteomics to emerging other fields of omics. champion for each vertical and -Major commitment to translational research from lab to sub-specialty. clinic.
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-Electronic Health Records (EHR) foundational but must improvise for genomic-data management limitations. F3. As the exemplar, oncology -Oncology was initial pathway, but now precision medicine is migrating to other specialties. must absorb precision medicine -For oncology, precision medicine is absorbing into into routine and self-directed routine practice independent of program administration. practice and not rely on the -Biobanking was foundational in two of the three precision medicine staff institutions. Improvisation and catch-up characterized the infrastructure for permanent third. -Precision medicine not seen as a universal solution. guidance and administrative -Precision medicine is a work in progress for most support. specialties and will evolve over decades, next generation challenge. F4. Precision medicine as a -Transition to precision medicine is happening slowly and clinical science is still a work in not in a scalable way. progress and will remain so for 9 What are the -Given the complexity and costs there will be a gap at least a generation. The human and between the haves and have-nots. -Significant annual financial investment required (in tentative nature and limitations financial aggregate the three institutions allocate > $100 million. for informing clinical practice resources -Range of dedicated professionals at the institutions is 200 reinforce the skeptics. required? to 550. -All positions were newly conceived and designed. Genomics/proteomics will not be -Hierarchical in structure; lateral in practice. the full answer. Integration with -Progress drivers: other emerging fields of omics, -Sequencing at scale e.g., epigenomics, metabolomics -Huge data input is necessary to complete the -Unprecedented levels of collaboration -HR needs transcend laboratory scientists molecular medicine paradigm -Wholesale creation of bioinformatics capacity shift. -Wholesale creation of pharmacogenomics capacity F5. Technologies and systems 13 What are the on- -Interwoven with focus on patient centricity. for comprehensive and going scientific -Migration into other clinical verticals. specialized genetic and other -Development of genomic risk scores and clinical -IRBs becoming more sophisticated omics testing must emerge from research -Bottomline results and directions for physicians ordering translational efforts at the objectives? tests. Page 245 | 477
-Consolidate data and insights towards prevention. institutions practicing precision -Promulgation of results and findings is essential. medicine. New specialties in -Collaborate with private sector companies in genomics when sensible. bioinformatics and -Need alternatives to Randomized Control Trials (RCTs). pharmacogenomics are evolving -Resolve the wall between research data and clinically and are foundational to available data. precision medicine. -Testing and assays must be home grown and validated. -Bioinformatics is a bottleneck. -Cannot yet inform clinical decision making without F6. Precision medicine will exist reliance on biobanking and predictive biomarkers – must in parallel with existing clinical reach point of identifying durable responders. practices and will not serve as a -Must merge clinical data with genomic data in a way universal solution. In retrievable and portable with EHR. combination, it will over -To extend the paradigm, must focus on the part of the genome that is not encoded in coding the protein. predictive, preventative, and 16 What are the -Education efforts must be based on inputs and expression curative opportunities not education efforts of need from practitioners and patients; assumptions about currently available. Precision what they want are misguided. and what medicine is viewed as a guide, -Protocols must be in place for reporting positive results but it cannot usurp the art of measures support and variants to patients and their families. promulgation of -Genetic codes are alphabets and numbers and reports are medicine. the program not actionable in the same way as other laboratory results; internally and to must determine the balance between necessary physician patients? knowledge and recommendations for intervention. F7. Precision medicine, once its -Precision medicine is valuable only in combination with methods become first-lines of other traditional diagnostic tools. -Physicians do not want to find positive results but when care, will reduce episodic costs presented, value the ability to intervene – focus of of patient care but likely education. increase total care costs by -Building and maintaining trust with patients is virtue of extending life. End of foundational to precision medicine. life care, however, may be -Patients are variable and segmented as never before; physicians must move beyond habits. reduced. 20 What are the -Imperative is to determine what we are doing before we principal ethical inform patients.
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considerations -The promise of precision medicine often gets out in front F8. Openness to patient- historically and of actual practice. centricity and sensitivity to -Bioethics must be part of the decision-support structure. currently? -Patient data must still be protected from being the basis ethical complexity are for employment, social or insurance discrimination. prerequisites at institutional and -Bioethics and educational efforts must bring patients to a practitioner levels of care. point where they can make truly informed consent. -Testing in genetics often results in the need for stacking F9. The bottom-line of testing additional testing. -Center of the mission is aligning the interest of patients reports and information must be and their motivations with available clinical options expressed in a confident and framed in terms of patient expectations, hopes and directive way, with supporting accurate comprehension. back-up. In the realm of -Challenge is aligning what patients think they will get predictive and preventative care, with what physicians believe they can offer. -Ethics must inform the patient education process the reports must follow the -Ethics purpose is to assist in building an effective, patient throughout life to other compassionate machine; not serve as a watchdog. providers.
21 What has been -Precision medicine adoption will depend on seamlessly F10. Precision programs must the evolution of fitting with prevailing practice patterns. -Precision medicine is not just about finding a cause but be built on an ethical framework process flow and determining best management. that becomes part of the decision what associated support for the clinicians. issues have emerged? F11. Precision medicine adoption will depend on seamlessly fitting with prevailing practice patterns and enhancing the degree of assistance that the physician can provide to the patient. The institutions must design and support the programs for this purpose.
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4 What is the -Across the institutions there is emphasis on sequencing Category 2 asks about how C-2) Is it a degree of healthy individuals to find out if genetic information factors are causes or allows earlier detection and prevention of disease. cause or a penetration of -Precision medicine will be adjunctive to prevailing consequences across categories consequence of precision knowledge. of inquiry. Specifically, are the some other medicine into -When older patients are positive for variants, testing their derived conditions or category? integrated offspring is indicated. antecedents a cause or practice in -Clinicians resist the penetration precision medicine for consequence of the above the following reasons: oncology and 1. Responsibility for the information. factors? The observations of other fields of 2. Who will manage and share the information. the interviewees can be medicine? 3. Lack of expertise on some mutations. synthesized into the following 4. Concern about how the patient will view the findings: information. 5. Does it jeopardize my patient’s insurability? 6. Emotional upset for patient and family. 7. Fear of impact on workflow. F12. There is resistance by -There is over-expectation that precision medicine will physicians based on a series of become algorithmic. concerns relating to information -It will be helpful, but medicine is deeply human and responsibility, control, cognitive based – everyone is different: 1. What are they willing to accept in terms of therapy? management and sharing; lack 2. What are their personal views? of expertise on some mutations; 3. How does uniqueness fit into to care dynamic? concern about patient reaction 4. Precision medicine is a guide, but it cannot usurp the art to information and patient of medicine. insurability; fear of impact on -Migration of precision medicine from one clinical vertical to another was often like starting over. clinical workflow and referrals -Migration to other clinical verticals is often limited by management; and precision pharmacogenomics in that field. medicine will become -There is a preconceived notion of the value of genomic algorithmic. testing. -The bigger problem is transforming health care to a model where not every piece of care provided is charged F13. Precision medicine is for but there is a dilemma—genetic counselors can only migrating to fields beyond charge when there is a positive result even though they are oncology during the time active with every test. Page 248 | 477
-In precision medicine, more providers will be engaged precision medicine is becoming but this cannot be justified based on revenue. fully integrated into oncologic practice – the necessary 5 What is the -Patients with complex histories can often be provided evolution for the field. degree of better coordinated care once genetic markers are known. -Genomics allows a preventative response: physician buy-in -What do you want to do? F14. There is a preconceived according to -How do you want to diagnose? notion of the value of genomic specialty? -How do you want to monitor and follow it? testing, but the sum and nature -Where are the resources that you have? -How do we couple with EHR? of that value has yet to be -As a group practice we benefit from sharing in the established and articulated in information. any clinical vertical. -If the only factor were getting a positive result, the Reimbursement will be process would have failed. ambiguous until that is resolved. -The critical component is what gets communicated and how it is taught to provider and patient. F15. There are gating factors 10 What are the -Costs are still largely absorbed through institutional for the migration from oncology costs associated investment. to other clinical verticals based with any given -Reimbursement is pursued where it is allowed. on several factors for the -Public policy efforts are directed at coverage and physicians: the role of genomics protocol? reimbursement. -Precision medicine is evolving and while immediate costs in prevention in their specialty; are higher it is still in the process of proving that overall approaches to diagnosis and costs of care will decrease. intervention; available 11 What are the -Importance of convincing the payer arm that the results of mechanisms to monitor overall costs of testing are worthwhile. progress; ability to couple with -Cost of care per week is lower but total cost of care is administering a higher because patients live twice as long. EHR in their specialty; and, precision -Efforts underway to reduce costs of testing and passing possible actions based on medicine savings to patients and payers. positive reports of a mutation or program? -Fundamental decisions around the structure of the variation. program include how allocations will be made from the operating bodies for patient care F16. Institutions must plan on
considerable internal investment Page 249 | 477
in precision medicine for the foreseeable future to underwrite translational research activity and integration with clinical care until that infrastructure is complete and payers accept the value. C-3) What are 2 What are the -Early recruits were medical geneticists for facilitation of Category 3 asks what are the the intervening clinical reporting. Medical Grand Rounds were used to introduce intervening conditions between and reinforce possibilities. Introduced with large clinical conditions infrastructure facility scope. Initiated based on outcomes to demonstrate the causes and consequences? between the requirements? value. Foundation is a large integrated care system that is Specifically, what is the causes and patient centric. relationship between the causes consequences? and consequences of factors -Three divisions in genomics: that drive precision medicine? 1. Clinical genomics lab where through a cap and clean environment we can provide genomic based testing right The observations of the to providers and patients based on a proprietary data and interviewees can be synthesized medical records system. into the following findings: 2. R&D Translational Science Center for development or discovery of new technology, new methodology or new tests, or procedures: translate into clinical settings. 3. Shared Services – Clinical research to feed samples and F17. Precision programs must data to the TSC. be launched with the utmost deliberateness and coordination -Need a few people willing to get out ahead of the curve through strict project and try to figure out some of the questions about how the management methodologies information is made more digestible and which parts are implementable form a clinical perspective – a difficult across the dimensions of clinical undertaking. staffing, clinical program selection, administrative -Project management is foundational to any program; need support, and financial resource methodology and rigor with intensive documentation to allocation, all coordinated and prove success. Developed three clinical arms: integrated across functions. 1. Advanced cancer diagnostics. Page 250 | 477
2. Comprehensive program for patients with F18. Administratively, a best suspected Mendelian genetic diseases; included practice is to divide genomic familial exome sequencing for triangulation. 3. Preventative interpretation to determine healthy medicine into three operating population genetics. units directed at clinical laboratory services for decision -Investments in infrastructure are necessary across the support; translational science board: infotech and bioinformatics especially which may for the embodiment of new have to be home grown. -Early years should be focused on capacity building. discoveries into clinical use in -Precision medicine is set up with five translational real time; and, shared services programs and seven infrastructural, each with a program to make most efficient use of director and an operations manager. resources and bridge the gap -Translational programs address: pharmacogenomics, between clinical and epigenomics, the microbiomes, clinical genetics, and biomarker discovery. translational efforts. -Infrastructure programs are the biorepository, medical genome facility, IT, bioinformatics, bioethics, education, F19. There must be a standing and administration. effort to process information into clinically digestible and 3 What are the -Data assets and warehousing must go beyond available actionable forms. data and bio- EHR systems; ratio of data in EHR to proprietary systems is 1:3 bank -EHR was conceived for billing and operational tracking, F20. Initially there must be a infrastructure not research. triage of effort and resources requirements for -Advantage was early capture of aggregated clinical data. addressing clinical focus and precision -EHR is 75% of what is needed for research and services organization, e.g. medicine? innovation but is 25 percent of data volume; everything else is 75 percent of data value but 25 percent of the value. establishing clinical arms in -Universal need in precision medicine for data mining to cancer diagnostics, rare do genotype, phenotype correlations and other analyses to diseases, preventative discover new relationships between genes and diseases or interpretation, and strategy. individual variants and disease.
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17 What obstacles -The institution’s bonds of trust with its patients meant F21. Initial focus is on capacity were that withholding positive results from research was not building with allocations acceptable; protocols had to be reviewed and revised to encountered in allow reporting. towards infrastructural needs the development such as biorepository, of the precision -Physicians and patients are concerned about insurance or information technology and medicine emotional impact on family relationships. The pressures of bioinformatics, as well as program? practice and economics are overwhelming and lead to bioethics and education, which more of learned helplessness than burnout. -A systematic issue with many country-based initiatives is are foundational to a clinical that return of results are not built into the program. program.
-Medical schools teaching BS grads cannot have the F22. Development of the ability to adapt to precision medicine at the pace of real precision medicine research and progress. clinical toolboxes are still in -Precision medicine as practiced at different institutions progress thus requiring must be careful that it is not spread too thinly; niches must investment in translational be established and recognition of what can be done well is activity in pharmacogenomics, mandatory. epigenomics, the microbiomes,
-On a genomics report, the physician can read page 1, but clinical genetics, and biomarker there may be 50 pages. How do they cull through that? discovery. The education tasks surround preparation of the physician to interpret. F23. EHRs are a bedrock infrastructure in precision -The initial focus was on sequencing and bioinformatics. That created the challenge of recruiting computational medicine and must be accessible biology graduates which this institution does not train. within the institution by all providers as well as referring -The precision medicine program developed a business physicians outside the plan early with the emphasis of organizing five institution. Institutions must translational programs and seven infrastructure programs. Initial mistakes were extensive but were made to be implement integration of genetic positive learnings. Carefully designed projects that were data with EHR is a searchable achievable around which people could rally with project fashion and with prompts that indicate a genetic basis for Page 252 | 477
management guidance; deliverables were carefully changes in a patient’s on-going defined, and progress monitored. health status.
-Leadership made decisions readily but preferred to be proven long quickly rather than defer decisions; avoided F24. Establishing and making decisions too late to have an impact. Mantra: start maintaining bonds of trust with small – move quickly – make decisions. patients are foundational to precision medicine and must be managed with transparent disclosure of genetic information, its interpretation, and implications throughout life.
F25. Medical school curricula has not kept pace with the developments in genomics and precision medicine, a factor that must be addressed.
F26. Recruitment and development of technical support in information sciences and bioinformatics has been a bottleneck. C-4) Within 6 What are the -The only markers used in the project are the mutations Category 4 asks within what what context relevant clinical identified by the American College of Medical Genetics as context does a category having high penetrance – all of these have medical does this dynamics actionability. A clear functional mutation of BRCA gives a emerge. Specifically, within category associated with 60 – 80 % chance of breast cancer compared to 12 % risk what context do the conditions emerge? precision for an average woman. Intervention is based on disease and antecedents emerge, i.e., Context refers medicine for trajectory. Hot links on the genetic reports go into depth. what is the setting and to the location incorporation dynamics of the precision of events or into patient care? medicine phenomenon? The Page 253 | 477 incidents -Patient consultation time is managed to allow discussion observations of the interviewees pertaining to a of results with the patients and the participation of genetic can be synthesized into the counselors. Physician offers creation of a family tree. phenomenon. Genomic patient conferences provide clarity and engage following findings: all whenever possible. The entire clinic has to “own” the patient – a work in progress. Physicians are offered alternative approaches to communicating with their patients with positive reports.
-Have introduced the principles of implementation science so that we do not rely on the passive diffusion of F27. Clinical interventions must knowledge. Implementation of precision medicine is also be limited to those mutations that about acculturation and engineering. The idea that you can are deemed to have medical go to a CME course or can read journals and somehow actionability and taken on the keep ahead when there are shifts in pathophysiology are illusory. This reality is not necessarily a threat but basis of disease trajectory. certainly creates a sense of fear: “how am I going to manage in this new paradigm?”
-When treating cancer patients, the physician gets frustrated that once a certain point is reached, there is nothing else to offer. Cancer care is also trial and error; responders cannot be predicted but it takes months to find out and must live with side-effects. F28. Patient education and communication is key and must -For implementation of precision medicine, competition be factored into consultation can be used to spur people from their usual practice. Data can be persuasive and shared among the in-house time by the attending physician providers. Until data is front and center you do not and supporting providers. understand if there was an issue or a problem. Willingness is a prerequisite to change, otherwise it is a waste of time. Systems evolve in medicine based on someone championing change. Change is a function of the constant feedback that is given on the way we practice, as well as changing and implementing new processes and new science.
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F29. Principles of -It takes effort mentally to get to a point of, “I’m wanting implementation science are to do precision medicine because I’m confident I can help more patients in this setting, and I’m not going to wait for necessary to promote active a randomized clinical trial while patients are passing integration of the care systems away.” We measure objectively that our patients are living and active diffusion of longer with greater quality of life with precision genomics. knowledge. A spirit of constructive competition must -A key factor in stabilizing medical oncology was to base incentives on quality and access, not upon administering also be promoted as a means of infusions of drugs. Alpha figured out how to align driving innovative standards and physician-incentives to reduce the burden of fee for behaviors. service and the churning of patients. Fee for service is antagonistic to precision medicine where the right drug for a patient must be provided regardless of the finances and incentives.
-It is not just the concentration of scientists, expertise, and skill, but enough shared vision. Have expanded into all clinical verticals in our system and are working with verticals leadership to implement precision medicine initiatives. F30. There must be a cultural -Have found two kinds of physicians: and operational shift of the 1. Innovative and forward thinking, inquisitive. incentive structure away from 2. Opposite of that. fees for procedures or drug To implement, find a champion and build consensus with infusions towards outcomes collegial review boards. Incorporate a summary or dashboard to highlight the specific drugs of interest with measurement as a condition of the associated pharmacogenomics, back-up in PDF. Think transformative change. more about leapfrogging – the decades of dogma in medicine makes PM adoption slower. Foundational pieces of pharmacogenomics are underway; seeking ways to incorporate discrete results into the EHR.
-The current traditional pathway is disrupted by precision medicine, but we lay the reporting of the test results and interpretation on the traditional pathway. Created a parallel Page 255 | 477
path for specimens for clinical and research purposes in F31. Migration across clinical order to have a proof principle that could achieve verticals relies on engaging comparable results. Also learned that there’s diversity in how that data is interpreted in those clinical laboratories innovative specialists in and what is returned. There was also variation in clinical leadership roles and the building interpretation which became apparent from parallel of consensus in collegial review analysis. Interpretation challenges emerged in both paths. boards. Does the result really reflect the condition of my patient? What do the results mean? For example, if it is a single variant in a recessive condition where only one of the alleles is disrupted, what does that mean? Data is vetted by genetic counselors and then geneticists would decide. The reality is that you need a cadre of individuals – a group F32. To overcome the impact of expertise that somehow fits between the clinical disruptions to the traditional laboratories and the physicians that were going to tease out the information. care pathway, test results and recommendations must be -Building synergies among services. Created an internal superimposed on the traditional board to take data, re-examine it and look at genetic care pathway but in ways that variants of unknown significance and doing functional anticipate and process variations studies to get an answer. in clinical interpretation. -An initial mistake was the belief that we must teach physicians about genomics – not a productive move. What F33. Precision medicine relies we report today tells part of the truth but as a clinician you heavily on building synergies are always dealing with part of the truth. Science cannot among clinical services as explain yet most variants, a role for machine learning and augmented intelligence. Work is perpetually collaborative. related to the interpretation and utility of data and not -Results are provided in a usable form and have quantified necessarily on the teaching of clinical judgement using standardized rating scales. Has the underlying genomic science. enabled within a brief duration a visible range of improvement.
15 What is the -When best practice guidelines are built into clinical status of decision support tools in the EHR, the default follows the best practice guidelines. Departing from the guidelines is Page 256 | 477 formation of more work than following them. Variability drops – a F34. Best practices are evolving precision good discipline for precision medicine. The precision over time and should not be medicine value is in the predictability of response to medicine as the therapy. It provides disease recognition prior to dogmatic, but as they are standard of progression and symptoms. formulated and accepted, they practice in should be incorporated into patient care? -Precision medicine challenges the way we look at, clinical support decision tools in interpret and follow clinical guidelines. It illuminates the order to reduce variability in the response to medications. More consistency and customizable to have specific guidance or treatment. Goal type of response and increase the is to customize to get to the best endpoint. predictability of the testing.
-Use care networks to expand the base of patients among like-minded institutions for re-examination of clinical guidelines. Instead of one gene seen in one patient in one institution, can have similar patients in various institutions. Can compare outcomes and response to drugs; move from an n of one to 20, etc. Networks or consortiums will become more popular.
-From a physician’s point of view, if the standard of care is followed, there is no blame but, what if the standard successfully treats only 30%? If I have a method that does massively better in the face of a standard, an adverse effect in the non-responders is seen as fault. Precision F35. Cross-institutional care medicine must work in a different system than the current one where it does not work optimally. The current system networks are necessary to does not have the capacity to treat one cancer patient at a expand the base of patients in the time, but it has the time to lose once cancer patient at a formulation of clinical standards time. and guidelines, and ultimately the scope of effectiveness of the -The big idea emanating from a [special] grant was how to make pharmacogenomics part of a standard of care when interventions. not everybody has the testing or patients that need the testing. Sequenced 11,000 people and release data into practice where there is discussion. Consulting EPIC for Page 257 | 477
each patient to see if there is a study underway is not yet a standard of practice for clinical pharmacologists. F36. Pharmacogenomics must
-Standards of care are often driven by inertia. The be positioned as part of the information is there for the entire team to open but many standard of care which has have not yet taken that step. Strategy is to create a implications for the training, confidence that the access is there. If the physician cannot hiring, development and use it, support is available for interpretation and decision retention of professional staff. that creates a sense of enablement. Rate studies show that 99% of patients have an actionable result if not now, then in the future. Getting providers to interact with that information is the critical first step.
-The critical moment of adoption for this practice across the rest of the world will be when it is a vended product. When a knowledge vendor has a product that incorporate this concept to them means something on which the clinician must act. Test results must be as direct and interpretable as prevailing chemistry and other assays.
C-5) Is this 7 Are formal -In pharmacogenomics most people have variants in genes category a clinical protocols that affect drug metabolism rates to help get the right Category 5 asks is this dosages: fast metabolizers need a higher dose. We are contingency currently in moving towards regular use. In primary care, “Okay, what category a contingency (having (having a place or are can we do next? How can we make that better? How can a bearing on another bearing on protocols a we standardize this?” category)? Specifically, what another work-in- factors affect changes in the category)? In progress? - “It’s far too soon to have clinical guidelines or standards antecedents or conditions – of practice for precision medicine. It would actually other words, inhibit practice.” especially the pace – for the what is change adoption of precision in this category medicine? The observations of dependent -There are groups that simply do not believe that there is the interviewees can be upon? enough evidence that pharmacogenetics has any place in synthesized into the following clinical care. Must move to standard clinical trials. Drug testing in pharmacogenomics is different. findings:
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-There is a growing desire for precision medicine adoption. The implementation of testing into practice is the challenge. Not yet incorporated into guidelines. No F37. Evolution of standards of major studies for clinical utility to say this is the position practice in precision medicine is where tests should be used. Often a challenge in bridging in its early stages. Acceleration and returning patients to the referral source. Conservative of the process risks stunting physicians expect to stay within guidelines; must have development of the field. The demonstration of clinical utility, but patients are pushing providers to that territory. process for the formulation of 8 What is the Provide resources to learn abnormalities quickly. Take it standards of practice is itself process for stepwise: sentences to paragraphs to additional material. It still addressing the clinical is gradually integrated. There is implementation from the processes and milestones internal protocol lab side: part of the regular test ordered through EHR, development and necessary to drive the gain insurance company support, if interpretation is formulation, testing and assessment? difficult, consult lab colleagues, develops a culture of dialog across services. adoption of standards.
-To align strategic goals, created a list of metrics that matches goals to metrics. Organized learning from mistakes. To have a playbook need internal investment: access to good laboratories, invest in education top to bottom, computational team must understand underlying F38. Reimbursement issues not data, the genomics, and translational omics. There is only reside at the payer levels emphasis on connectivity of systems which is but must be driven by physician infrastructural as well as scientific. practice and preferences for the use of precision medicine tools. 12 What are the -Pushback tends to happen with genomics at the start of Payers are looking towards issues with the process of care. The reticence for impact or clinicians to set the pace of insurability is passing because people are getting payers for sequenced widely. Physicians are not pushing back and adoption and demand in order to reimbursement? are becoming advocates with payers. justify reimbursement; innovation must be the province -Have allowed the sequencing for 60 selected genes for a of the physicians, not the payers. population of patients free of charge through the health plan to establish a baseline.
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-Publication of results in a [peer reviewed] journal helped convince payers. That process must be replicated widely. The article showed that the offset of the much higher pharmaceutical costs was from the dramatic reduction in the end of life hospitalization. Open question: is that a function of molecular intervention or richer engagement and earlier discussions with patients?
-How can we either reduce our costs or improve our F39. Cognitive limitations testing to provide competitive advantage? The emphasis is surrounding assimilation and on learning from physicians why or why not choosing this implementation of data by type of testing. physicians is an obstacle for the implementation for precision -Most telling statement is that “We don’t want to be an outlier or on the front end of the innovation curve.” medicine and must be addressed Translation: “We want to cover what other payers are by support from genetic covering and we don’t want to cover what nobody else is counselors and covering.” That reasoning produces a regression to the pharmacogenomics in the mean. current environment and over
-Payers are the least innovative aspect of health care time with expert systems. because market forces and incentives are misaligned. Systems must then accommodate Must take a two-pronged approach: 1. Most payers will towards providing therapeutic follow Medicare – approach with Medicare is to provide value within the traditional care data and information, creating relationships that inform. 2. pathway. Working directly with other payers, including our own, and educating them. Slow process that often does not feel hopeful. As important is working diligently and demonstrating reduction of sequencing costs so that we can test even without a payer. It is as much about the choice of therapy as the diagnostic.
-An entirely new model, especially on the therapeutic side of precision medicine must evolve for paying now for something that affects a lifetime.
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18 What are the -Physicians must make decisions as to what happens or obstacles in the does not happen. Limitations are defined by cognitive capacity around data. Biggest revolution will be around current expert systems – computers are outperforming radiologists development and and pathologists in diagnostics. The impact of combining expansion of the computers and clinicians is unknown. precision medicine -Response to physicians dubious about precision medicine: “Well, if we understand how you do your work, and we program? understand your workflow, and we understand how you F40. There is community use your EHR, we can present this information to you concern that the use of precision right when you need it so that you can use it to make a medicine tools may proliferate at better decision about how to cure for the patient.” a pace that is beyond the capacity of a given health system -The essential nature of the conflict: If a cardiologist is told you need to order pharmacogenomic testing of to respond or to meet the anybody being considered for [specific drug] because 15% necessary infrastructural of Caucasians cannot convert it into an active ingredient. If requirements for broad access you want best care that is a test you need to do. The by physician and patients. This cardiologist replies, “The evidence is insufficient. There’s must be addressed through ten times more evidence for adjusting the dose based on administering a proton pump inhibitor, which is done deliberate planning and regularly.” Another way of replying: “I’m the professional forecasting and supported by and this is how I was taught – I make and live with the adequate financial investment at decisions.” Or, it is really about: “Leave me alone. I want each provider. to practice the way I want to practice.” Should outcomes be sacrificed to maintain autonomy?
-We are still at the front-end of a long journey. Currently there are limitations on what drugs and treatments are offered but that will change with better understanding of the genome. -With precision medicine we can move upstream to practice preventable medicine. If 15% of cancer comes from an inherited germline mutation, we are not capturing them. Too many young patients present with metastatic disease that we should be able to know in advance. Page 261 | 477
-There is a concern at many institutions that precision medicine can snowball to the point where the institutions will not be able to scale-up adequately to meet the needs and demands. There are not enough academically prepared people. Precision medicine is the right thing to do. The best course of action is for collaboration to happen and not have local groups unable to leverage knowledge and experience it across these platforms.
-Fear of scale requirements and related costs. Looking at a kind of modular turnkey—hospitals choose what is needed and what they will do. Does this institution can evangelize precision medicine and provide support services? Rationalizing and selecting from multiple tests doing the same thing; determining clinical sequencing platforms (internal or commercial) in any given circumstance. There are differences on different tests. Reliability is variable. Big general test versus specific gene tests. Not one size fits all.
-It takes well-trained and well-intentioned physicians many years before genomic medicine flows seamlessly into practice. Genomics, and omics testing in general, is part of a strategy for offering out to others. Still at a point where such testing is not remunerative. Companies offering testing subsidize the charges in exchange for data. Critical aspect is a marriage of a rich base of medical records with genomic data. Challenge is translating to clinical relevance because many physicians are not yet buying the benefits. Those resisting ask the question, “How am I ever going to incorporate this into my practice given the way medicine is structured? How am I going to have access to all the experts I need at every level to interpret this?”
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C-6) Is there 14 How is the -Comparison of physician outcomes – in an anonymous Category 6 asks is there covariance monitoring and but privately disclosed way – was a valuable way to covariance between this change practice. The program is still too young to do between this measurement of interventional clinical trials; not engaged in first in human category and other categories? category and outcomes trials. Specifically, what is the other managed? strength of the correlation of categories? -Working towards consistency across the system. Follow a precision medicine antecedents value-based care model across the system but still need to and conditions with other do more outcomes research and clinical utility studies to convince payers of test efficacy. factors governing medical practice? The observations of -Still evolving a consistent process for monitoring patients the interviewees can be being tested across the system. Focus on creating synthesized into the following awareness among providers of test availability and ways of findings: ordering; ordering trends are positive for penetration of precision medicine. There can be spikes in ordering; follow-up needed to determine the response to the structure and content of genetic reports and the clinical value of the information. -Specific metrics: -What were the results? -Are there correlations? -If not followed, why? F41. Practice parameters can -What changes were made, and why? change through comparison of outcomes among physicians if -Clinical programs represent different disease areas there is consistency in applying making the task to identify care process models for monitoring and measurement consistent use throughout the system. The leaders of the clinical programs want to know specifically with evidence frameworks consistently across a when the testing occurs and the postulated associated system, e.g., characterization of benefits to indicate when testing is recommended, e.g., results, establishment of tumor sequencing has inserted next generation testing for correlations, follow-through on every newly diagnosed stage-four cancer patient. therapeutic recommendations,
-Currently creating outcomes data to identify specific and the kinds of changes in patient benefit but still using a shot-gun approach: clinical behavior. capturing prescriptions received, returns to clinic, re- admissions, ER visits, re-hospitalizations, and other Page 263 | 477 factors. The inherent difficulty is that analysis has been retrospective which introduces confounding variables.
-Seeking to move to randomized controlled trials (RCTs) where cohorts are in protocol or not. Attempted RCTs with pharmacogenomics but the Institutional Review Board (IRB) tabled the application; IRBs are catching up with the science here and elsewhere. “The idea is to keep trying different angles to get to the gold standard approach. For now, it is a retrospective data pull with different endpoints to see what might be in the data. That might drive what a clinical trial might look like in the future that can be controlled.”
-Positive impact of an interim program assessment drove both the administrative and payer sides towards continuation and expansion of the program. Regular F42. Randomized controlled reporting is part of the annual budgeting process. trials (RCTs) are a prerequisite Simultaneous to institutional support growth there was a for comparison and grassroots movement among patients and philanthropists determination of effectiveness of providing support; served as a surrogate for objective outcomes. It took three years to generate documented precision medicine. RCTs will objective outcomes beyond the patient-physician drive further clinical adoption, experience, community enthusiasm and other intangibles. reimbursement, and systematic derivations of standards of -Oversight requires that outcomes be captured – not just practice. clinical or research outcomes, but outcomes of the overall precision medicine project. In addition to meeting goals, we are asked “What did you learn from this?” Emphasis on learning from success and failures.
-Documentation over the years also includes a series of outcomes, i.e., the number of publications, presentations, policy interventions, abstracts, posters, new articles, placement on boards and committees, and the like as benchmarks for program impact. Metrics continue to evolve with the growth of the program. Page 264 | 477
Discussion and Conclusions from Interview Findings Restatement of the Arguments and Research Questions of Study 2
The investigation and related arguments of Study 2 focused on the necessary conditions for the implementation of precision medicine and the clinical resistance to such implementation, and the ways that such resistance has been managed at three of the leading American precision medicine providers, again designated herein as Alpha, Beta
and Gamma. In addition, the design of Study 2, the selection of interview venues and
interviewees, and the structure of the interviews explored implications for theories
surrounding resistance to change in organizations and professional communities during
circumstances of a Kuhnian scientific or clinical paradigm shift.
In summary, the three arguments of Study 2 that were stated previously are:
• One, clinical resistance to precision medicine exists and that there are
determinable and operationally manageable reasons for this resistance.
• Two, that the managerial strategies in place at leading institutions are definable
and reproduceable in other clinical environments.
• Three, observations concerning resistance to precision medicine and their
management have implications for theories of organizational change.
In order to address these arguments, the Research Questions of Study 2 were previously posited as:
• Research Question One: Foundational concerns -- What are the antecedent
conditions for precision medicine to be incorporated into strategies for care
delivery and guidelines for professional practice?
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• Research Question Two: Provider readiness – How is precision medicine
positioned operationally to be incorporated into patient care generally as based
on cultures and systems established at exemplary institutions?
Research Question 3: Change dynamics – What are the implications of the
pace of adoption of the precision medicine paradigm at the exemplary institutions for the field of organization theory, in particular, its subfield of resistance to change?
This section of Study 2 will describe how the three arguments are successfully satisfied through the findings generated through the analysis of the interviews, and how the three research questions are answered.
Grounded Theory Families and the Cascade of Issues
Structure of the interviews and the theoretical coding using the “Six C” coding families of Grounded Theory prompted several interrogations of the data and associated categories to help clarify their relationship with one another. Those families and the associated questions are as follows:
• Family C-1) What are the conditions or antecedents to adoption of precision
medicine as formulated and implemented at the three leading American
institutions?
• Family C-2) How do the articulated conditions or antecedents serve as factors
across categories of inquiry. Specifically, are the derived conditions or
antecedents a cause or consequence of the implementation of precision medicine?
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• Family C-3) What are the intervening conditions between the causes and
consequences? Specifically, what is the relationship between the causes and
consequences of factors that drive precision medicine?
• C-4) Within what context does this category emerge? (Context refers to the
location of events or incidents pertaining to a phenomenon (Strauss & Corbin,
1990)). Specifically, within what context do the conditions and antecedents
emerge, i.e., what is the setting and dynamics of the precision medicine
phenomenon?
• C-5) Is this category a contingency (having a bearing on another category)? In
other words, what is change in this category dependent upon? (This refers usually
to unplanned change (Strauss & Corbin, 1990; Swanson, 1986)). Specifically,
what factors affect changes in the antecedents or conditions – especially the pace –
for the adoption of precision medicine?
• C-6) Is there covariance between this category and other categories? (Covariance
occurs when one category changes with the changes in another category without a
causal connection (Strauss & Corbin, 1990)). Specifically, what is the strength of
the correlation of precision medicine antecedents and conditions with other factors
governing medical practice?
The matrix in Table 22 above details the relationship of the families, the associated themes and nodes processed using NVivo and conventional visual text analysis. The text analysis criteria for frequency of an expressed observation or idea was that there be at least five such mentions by at least two of the three institutions. The characteristics of the observations or ideas were reformulated and articulated by this
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author as Findings which are then used to establish Propositions. The families neatly
demonstrate that the recurrence of observations and ideas by interviewees yielded a total
of 42 Findings that fulfil the inquiry associated with the research questions and the
arguments of this study. The relationships among the arguments, questions and Findings is characterized in Table 23 below.
Table 23: Relationship of the Findings to supporting the Arguments or answering the Research Questions of Study 2 Arguments Supporting Findings A1. Clinical resistance to precision Group 1 (26) Findings: F2, F4, F6, F9, medicine exists and that there are F11, F12, F14, F15, F19, F20, F22, F24, determinable and manageable reasons for F26, F27, F30, F32, F33, F34, F35, F36, this resistance. F37, F38, F39, F40, F41, F42 A2. The managerial strategies in place at Group 2 (18) Findings: F1, F3, F5, F7, leading institutions are definable and F8, F9, F10, F11, F13, F16, F17, F18, reproduceable in other clinical F19, F21, F23, F28, F29, F31 environments. A3. Observations concerning resistance Group 3 (25) Findings: F2, F4, F6, F12, to precision medicine and their F13, F14, F15, F19, F20, F22, F24, F25, management have implications for F26, F27, F30, F31, F33, F35, F36, F37, theories of organizational change F38, F39, F40, F41, F42
Research Questions Answering Findings RQ1. Foundational concerns -- What are Group 4 (22) Findings: F1, F5, F6, F8, the antecedent conditions for precision F9, F10, F11, F13, F15, F19, F24, F27, medicine to be incorporated into F30, F32, F33, F35, F36, F37, F38, F39, strategies for care delivery and guidelines F41, F42 for professional practice? RQ2. Provider readiness – How is Group 5 (22) Findings: F1, F2, F3, F4, precision medicine positioned F7, F8, F9, F10, F11, F15, F16, F17, F18, operationally to be incorporated into F19, F20, F21, F22, F25, F28, F29, F31, patient care based on cultures and F34 systems established at exemplary institutions? RQ3. Change dynamics – What are the Group 6 (29) Findings: F1, F2, F4, F6, implications of the pace of adoption of F9, F11, F12, F13, F14, F15, F19, F20, the precision medicine paradigm at the F22, F24, F25, F26, F27, F30, F31, F33, exemplary institutions for the field of F34, F25, F36, F37, F38, F39, F40, F41, organization theory, in particular, its F42 subfield of resistance to change?
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It is worth reiterating that Grounded Theory is an inductive, not a hypothetico- deductive approach to investigation. The grouping of the Findings, which are derived from the interview observations according to the criteria described above might resemble the conventional alignment of data in support of hypotheses. This research, however, is not built around hypotheses but seeks to structure input organized around existing approaches to precision medicine, as derived in Tables 21 A, B and C, and then consider the input from interviews to support arguments and answer research questions.
This research was not designed to validate or disprove a posteriori notions about the antecedent factors or conditions for the implementation of precision medicine, but to discover what factors are in play a priori – thus the benefit of a Grounded Theory approach. Moreover, the objectives of this research include a determination of whether and how physicians are resisting change associated with precision medicine, and how the basis of that resistance might inform prevailing theories of resistance to change in organizations.
The interview questions were formulated to be open-ended and not lead the interviewee towards a conclusion. Rather, the questions allowed the interviewee to reflect on the phenomenon and factors associated with their own experience with precision medicine. The association of the Findings in supporting the arguments of this dissertation or in the answering of the research questions of Study 2 are particularly robust. More can be ascertained in examining the Propositions that are derived from the
Findings.
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The Findings, Propositions, and their Implications
Six Propositions were derived from the 42 Findings based on a determination of extracting testable hypotheses for future research concerning the transferability of
Findings to other institutions. In order to examine closely the relevance and thrust of the
Propositions, they are grouped into three categories, each with different implications.
The three Proposition categories are:
Category 1 Propositions (Table 25): Incorporating scientific and clinical antecedents and
conditions for other institutions.
Category 2 Propositions (Table 26): Incorporating operational propositions for other
institutions.
Category 3 Propositions (Table 27): Incorporating change management propositions for
other institutions.
Discussion of Category 1: Incorporating scientific and clinical antecedents and
conditions for other institutions. Those Group 2 Findings in Table 23 that supported the
argument that the managerial strategies in place at leading institutions are definable and
reproduceable in other clinical environments were derived from statements made by
interviewees throughout their comments. Similarly, those Group 4 Findings that
addressed foundational concerns, i.e., the antecedent conditions for precision medicine
to be incorporated into strategies for care delivery and guidelines for professional
practice were also drawn from comments made throughout the interview transcripts by
the interviewees. This argument and this research question specifically address the
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Table 24: Comparison of precision medicine related factors at the three institutions Factor Alpha Beta Gamma Year precision 2006 preliminary; medicine established 2011 2012 2012 formal Role of CEO in PM Prime mover Highly supportive Prime mover Legal status Private/non-profit Private/non-profit Private/non-profit Type of hospital Regional Resource Regional Resource National major care Medical Center/ Medical Center/ provider/Quaternary Quaternary care Quaternary care care Physicians on staff 2000 2400 4500 Employed or Employed – clinic Employed – clinic Employed – clinic contractors structure structure structure Patient census 3 million patients 550,000 1.3 million Medical School Operates own Affiliated with a Operates own university Electronic Health >25 years; fully >25 years; fully >25 years; fully Records (EHR) integrated; genomics integrated; genomics integrated; genomics separate separate separate Biobank >50 years; integrated >20 years; integrated >50 years; integrated with EHR; with EHR; with EHR; comprehensive use comprehensive use comprehensive use with patient with patient with patient population population population Patients sequenced >100,000 >100,000 >100,000 Annual investment Annually tens of Annually tens of Annually tens of in precision millions of dollars millions of dollars millions of dollars medicine not subsidized from subsidized from subsidized from reimbursed by general operational general operational general operational patient care budget and budget and budget and philanthropy philanthropy philanthropy Research culture and Extensive clinical Extensive clinical Extensive clinical thrust research research research and translational research of internal developments Non-oncology Growing beyond Growing beyond Active across applications oncology oncology specialties Established as Work in progress but Work in progress but Work in progress but standard of care feel that standards feel that standards feel that standards would be too soon would be too soon would be too soon Broad range Capturing tens of Capturing hundreds Capturing hundreds sequencing programs thousands of thousands of thousands underway Ethical oversight At origination and At origination and At origination and significant oversight, significant oversight, significant oversight, IRB closely reviews IRB closely reviews IRB closely reviews new protocols new protocols new protocols
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adaptability or generalizability of the experiences at the three leading institutions
studied. The significance of the generalizability is a factor in this analysis because the
three institutions interviewed are remarkably similar in organizational structure, clinical
services organization, relationships with physicians, care and patient journey culture and
many other factors. Table 24 demonstrates the congruity of the institutions on several
critical measures in precision medicine.
The similarities and uniqueness of these institutions in terms of clinical
philosophy, structure, capabilities and culture – especially considering their leadership roles in precision medicine – invites speculation that their underlying organizations are themselves superordinate conditions for the implementation of precision medicine and that other institutions falling outside such a structure are disadvantaged or disqualified from full implementation of precision medicine. The cited Propositions, therefore, must be examined to determine any prerequisite organizational requirements.
Propositions derived from Findings Groups 2 and 4 in Table 23 are uniformly adaptable to health care organizations irrespective of design and would not be dependent on having structures or cultures similar to Alpha, Beta and Gamma.
The sampling of three Findings in Table 25 can be repeated for all the Group 2 and 4 Findings, thus demonstrating that conclusions drawn from the interview satisfy the argument that the managerial strategies in place at Alpha, Beta and Gamma are definable and reproduceable in other clinical environments. Moreover, the first research question of Study 2 – What are the antecedent conditions for precision medicine to be incorporated into strategies for care delivery and guidelines for professional practice? – is populated with viable and universal principles as expressed in Propositions 1 and 2.
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Thus, Argument 2 of the dissertation: QED – the managerial strategies in place at
leading institutions are definable and reproduceable in other clinical environments.
Table 25: Universal applicability of selected Group 2 and 4 Findings in Table 23 and the derivation of Propositions Findings common to Groups 1 and 4 Category 1 Propositions: Incorporating clinical antecedents and conditions for other institutions. F. 1 The implementation of precision Proposition 1: For success, an institution medicine at an institutional provider is must have access to enough human driven top down initially but developed resources and financial capital for bottoms-up with significant, diversified implementation over the long term and human resources supported with reliable there must be optimum efficiency of financial commitment over the long-term. internal communities of practice through cross collaboration. Corollary: The dynamic of top down leadership shifting to bottoms up leadership is a function of style, not structure. There is nothing organizationally inherent in the ability to establish this modality of cooperation. F.9 Bottom-line of testing reports and Proposition 2: Clinical reports that information must be expressed in a integrate care strategies with genomic confident and directive way, with data are foundational to successful supporting back-up. In the realm of implementation. The structure and design predictive and preventative care, the must allow reports to follow the patient reports must follow the patient through their care journey, especially at throughout life to other providers. other providers. Operationally, there must be integrated activity and collaboration F. 19 There must be a standing effort to between the pathology function and the process information into clinically clinical services to a degree that surpasses digestible and actionable forms. traditional relationships and protocols. Corollary: Formal collaborative efforts among providers and EHR vendors are essential. Communities of practice must promote integration of the pathology and pharmacy functions with decision making for disease intervention.
For Research Question 1 of Study 2 concerning foundational concerns – What
are the antecedent conditions for precision medicine to be incorporated into strategies for care delivery and guidelines for professional practice? — The interviews, Findings
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and derived propositions validate that there are essential and definable elements of implementation that can be replicated.
Discussion of Category 2: Incorporating operational Propositions for other institutions.
Looking again at Table 23, the Groups 1 and 5 Findings address operational transferability to other institutions. The Findings address the argument that clinical resistance to precision medicine exists and that there are determinable and operationally manageable reasons for this resistance. Once clinical resistance can be characterized from the experiences of Alpha, Beta and Gamma, management at other institutions can plan for operational approaches to manage that resistance. Similarly, the Findings listed in Table 26 cluster around the questions related to provider readiness, specifically, is precision medicine positioned operationally to be incorporated into patient care based on cultures and systems established at exemplary institutions?
The Findings in Table 26 can be used to derive Propositions 3 and 4. These
Propositions suggest that conclusions drawn from the interviews satisfy the argument that clinical resistance to precision medicine exists and that there are determinable and operationally manageable reasons for this resistance. Alpha, Beta and Gamma encountered resistance as they developed their precision medicine programs but found operational solutions that are definable and reproduceable in other clinical environments. Moreover, the second research question of Study 2 – How is precision medicine positioned operationally to be incorporated into patient care generally as based on cultures and systems established at exemplary institutions? – is also answered with viable and universal principles.
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Table 26: Universal applicability of selected Group 1 and 5 Findings in Table 23 and the derivation of Propositions Findings common to Groups 1 and 5 Category 2 Propositions: Incorporating operational propositions for other institutions. F2. The practice culture must be flexible Proposition 3: Standards of practice and on the employment of standards of care clinical guidelines are developed and but ultimately must make evidence-based promulgated by internal communities of assessments. Oncology is the starting practice but ultimately for universal point, but precision medicine must applicability, but each physician and migrate to other clinical verticals swiftly, provider organization must adopt and ideally with the emergence of a champion evolve a practice culture unique to itself. for each vertical and sub-specialty. Clinicians and their provider institutions must determine how best to incorporate F.11 Precision medicine adoption will precision medicine into prevailing depend on seamlessly fitting with practice patterns. Corollaries: The prevailing practice patterns and practice of precision medicine enhancing the degree of assistance that accommodates essentially any care the physician can provide to the patient. culture provided that clinicians are The institutions must design and support flexible and base decisions on evidence. the programs for this purpose. This requirement is not associated structurally with an organization although the organization must provide leadership towards flexibility. Precision medicine does not necessarily require alteration of care and referral patterns, but the patient journey must take into account needs for effective precision medicine.
F. 31 Migration across clinical verticals Proposition 4: Administrative leadership relies on engaging innovative specialists and clinical key opinion leaders must be in leadership roles and the building of cultivated and schooled for the consensus in collegial review boards. promulgation of a precision medicine program with the validation of the community of practice. Corollary: There may be a difference between academic health centers and community hospitals in the adoption of precision medicine across clinical verticals. Migration across clinical verticals is sequential and determined by practice experience and the underlying nature of the diseases treated, i.e., are the diseases monogenic or polygenic?
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Thus, Argument 1 of the dissertation: QED -- clinical resistance to precision
medicine exists and that there are determinable and operationally manageable reasons
for this resistance. For Research Question 2 of Study 2 concerning provider readiness –
How is precision medicine positioned operationally to be incorporated into patient care
generally as based on cultures and systems established at exemplary institutions? –
conclusions from the interviews and related Propositions strongly support that the
experience of Alpha, Beta and Gamma can be translated to other institutions.
Discussion of Category 3: Incorporating change management Propositions for other institutions. The Group 3 and Group 6 Findings in Table 23 are uniformly adaptable to health care organizations irrespective of design and would not be dependent on having structures or cultures similar to Alpha, Beta and Gamma. As was done in the discussions of Categories 1 and 2, two Propositions can be derived from the findings listed in
Groups 3 and 6. The analysis and articulation of Propositions 5 and 6 appear in Table
27. Again, the conclusions from the findings satisfy the argument that the managerial strategies in place at Alpha, Beta and Gamma are definable and reproduceable in other clinical environments. Moreover, the third research question of Study 2 on change dynamics, i.e., What are the implications of the pace of adoption of the precision medicine paradigm at the exemplary institutions for the field of organization theory, in particular, its subfield of resistance to change? – is also populated with viable and universal principles. Thus, Argument 3 of the dissertation: QED -- observations concerning resistance to precision medicine and their management have implications for theories of organizational change.
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Table 27: Universal applicability of selected Group 3 and 6 Findings in Table 23 and the derivation of Propositions Findings common to Groups 3 and 6 Category 3 Propositions: Incorporating change management propositions for other institutions F4. Precision medicine as a clinical Proposition 5: Program leaders must science is still a work in progress and will acknowledge that resistance is partially remain so for at least a generation. The based on the belief that genomics and tentative nature and limitations for proteomics, although foundational, are informing clinical practice reinforce the not the total drivers of precision medicine skeptics. Genomics/proteomics will not be and that incorporation of the other the full answer. Integration with other “omics” are necessary to complete the emerging fields of omics, e.g., paradigm. Corollary: Precision medicine epigenomics, metabolomics is necessary is recognized as a true paradigm shift by to complete the molecular medicine clinicians and scientists at the three most paradigm shift. advanced institutions. Hence, they forecast that full implementation may be a generational exercise dependent on a combination of training future physicians and expansion of the necessary infrastructure as related fields evolve to the point of clinical utility. F. 13 Precision medicine is migrating to Proposition 6: Precision medicine fields beyond oncology during the time programs must encourage migration from precision medicine is becoming fully oncology across other clinical verticals. integrated into oncologic practice – the Corollary: The logical clinical venue for necessary evolution for the field. the emergence of precision medicine was oncology given the genetic basis of cancer and the ability to sequence the patient and the tumor. As cancer care is fully operationalized, deliberate efforts are needed for other areas of medicine.
For Research Question 3 of Study 2 concerning change dynamics – What are the implications of the pace of adoption of the precision medicine paradigm at the exemplary institutions for the field of organization theory, in particular, its subfield of resistance to change? While the elements relating to the management of resistance to change can be managed across most provider structures and cultures, there is some departure from prevailing theories of resistance to change.
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The relationship of resistance to change in the adoption of precision medicine
will now be observed for congruity and incongruity with prevailing theory.
By way of graphic illustration, Propositions 4, 5 and 6 can be represented by the
framework in Figure 16. The resistance to precision medicine is partially driven by
skepticism of the utility of the field across different specialties and disease sates. Those
diseases with specific genomic causality (monogenic), are generally recognized as
having the highest utility. Those that are polygenic are currently believed to have the
lowest utility based on existing technological capability.
Figure 16: Relationship between utility of precision medicine with disease state: organizational capabilities and therapeutic realities. Source: Haslem et al, 2018. Figure suggested by Ram Mudambi.
Healthcare providers (hospital systems) have differential capabilities with regard
to the operationalization of precision medicine, as captured by the left vertical axis. The
study focused on the three organizations identified as global leaders in implementing
precision medicine capabilities to obtain the trajectory of current applications (dashed
line in the figure).
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Precision medicine adds differential value added in different therapeutic areas, as captured by the right vertical axis. The frontier of value added from precision medicine depends on the extent of inter-personal disease effect and variability. Hence it is low in areas like diabetes (polygenic) and high in areas like oncology (monogenic) thus determining the shape of the dashed line in the figure.
Does Figure 16 suggest that the realm of precision medicine is limited to diseases characterized as monogenic or less complex genomically? That is not a reasonable conclusion. The convergence of the normal science of precision medicine with the normal science of the prevailing paradigm is a work in progress. The value and impact of precision medicine on polygenic disorders will evolve as clinical experience is accumulated and as the other omics become integrated with genomics. Alpha, Beta and
Gamma, among other institutions, are deliberately migrating precision medicine from its starting point in oncology.
Congruity of Findings with Organizational Literature on Change
As previously cited, Pardo del Val & Fuentes, 2003 posit the sources of resistance into five groups, each of which has an interconnection with the findings from the interviews:
1. Sources of resistance and inertia in the formulation stage which typically
emanates from a distorted perception of the proposed program and hence its
underlying need. While precision medicine has evolved beyond its
formulation stage, the Synthetic Paradigm of medicine remains the dominant
model of clinical practice. The interviews demonstrate that individual
clinicians and the health care provider institutions are still at the formulation Page 279 | 477
stage of implementation within their practice patterns and organizational
structures.
2. Low motivation for change driven by perception of costs and how they will
be accounted, experience with past failures or inconsistent expectations or
rewards for the involved employees (Rumelt, 1995; Waddell & Sohal, 1998).
As cited in Study 1 and the interviews with the three institutions, the practice
of precision medicine is still heavily subsidized and not yet fully reimbursed
by payers. As cited in the interviews, physicians are reluctant to take a
therapeutic approach the costs of which will fall on the patients.
3. Management’s lack of creativity in assessing the overall situation, fatalism
for achieving success or lack of a clear commitment (Rumelt, 1995; Waddell
& Sohal, 1998) is in evidence with most providers, even most of those
responding to the PMC Landscape Study. The interviews also indicate that
unless the institutional leadership is aligned with the clinicians, there is a
perceived lack of creativity or commitment to the extended demands of a
precision medicine program.
4. Sources of resistance and inertia in the implementation stage. Once
management undertakes implementation, additional resistance groups can
emerge. The resistance of physicians to implementation is not reflective of an
organized movement or constituency. There are no apparent political
deadlocks but there is still underway a culture of practice transformation of
indeterminate lengths. Other objections are related to the lack of evidence
that precision medicine makes a difference in outcomes beyond the
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experience in oncology. There were concerned regarding re-alignment of
decision support functions.
5. Resistances also emerged regarding established workflow and related
systems, as well as a concern of possible gaps in sustainable capabilities for
delivery of all supporting aspects of precision medicine.
These five dimensions provided a useful lens for the evaluation of data from the interviews.
There is also congruity with the second literature stream concerning the relationship of research and practice. Erwin & Garman’s (2009) review article observes that research-based guidance to organizational change agents and managers can address individual resistance to organizational change initiatives. Given the role of the individual physician practitioner in the acceptance and implementation of precision medicine in the face of research, there is consistency with the observations. The Erwin & Garman
(2009) characteristics can be further explored:
1. What are the key concerns of individuals upon the announcement of change
that influence resistance? These include self-assessment of competence to
deliver on new responsibilities associated with change, as well as perception
of the organization’s and co-workers’ competencies. (Giangreco & Pecci,
2005; Oreg (2006); Chreim (2006). These observations reflected a
continuous theme in the interviews.
2. What is the perception of personal benefits, risks, or threats? A consistent
theme was physician’s concern about maintaining control over the care
process and the perception of their competence resulting from increased
reliance on using other decision support professionals.
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3. How does engagement and participation in the change effort promote
participation or resistance? How are buy-in, assignment delineation, role in
approval or veto, feedback-loops managed (Giangrecco & Peccei, 2005)?
The implementation process at the most integrated institutions began with
one care vertical – oncology – and migrated into other verticals. The
practitioners outside of oncology inherited approaches in which they had
little input.
The framework derived from Erwin & Garman (2010) has utility in this dissertation in describing the interplay of organizations and individual attitudes and behavior; this interplay was explored in the interviews with the three institutions. For future research, the framework can be used to survey more deeply physician attitudes towards resistance generally and for the implementation of precision medicine.
The interview results are congruous with the third and fourth general theory literature streams described in the literature review, but the fifth and last is particularly relevant and concerns the changing nature of change resistance over time (Jones & Van de Ven, 2016). This research stream explores whether relationships between change resistance and its consequences and antecedents strengthen or weaken over time during an extended duration of organizational change. As stated previously, this is a significant question with respect to this dissertation because Study 1 asserts that given that precision medicine represents a paradigm shift, its absorption into science and clinical care will take place over decades or generations of medical practice.
Jones and Van de Ven (2016) found that resistance to change over time had increasingly negative relationships with two important consequences: employees’
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commitment to the organization and perceptions of organizational effectiveness. Based
on the interviews this also captures physician attitudes towards precision medicine and
there will be an unpredictable pace towards implementation across health systems as
postulated.
Jones & Van de Ven (2016) add that not all employees within a given organization respond alike to the changes ongoing in their organization. That represents physicians whether they be employees or contractors. While physicians respond with
enthusiasm others resist the changes (Caldwell et al, 2004; Thompson & Van de Ven,
2000). Still other are ambivalent (Piderit, 2000). There is congruency with the interview
findings of this research provided that “community of practice” is substituted for
“employee”. Conditional congruity is explored in the next section.
Incongruity of Findings with Organizational Literature on Change
The literature review included treatment of resistance to change in health care
and it is within that body of literature that there is the greatest incongruity with the
findings from the interviews with Alpha, Beta and Gamma. As was previously observed,
about 30 percent of physicians are currently in private practice. Another 30 percent are
in large group practices and about 40 percent are hospital employees (Physician
Advocacy Institute, 2019). Most physicians, therefore, still work based on “admitting
privileges” with hospitals and although subject to the rules and protocols of those
hospitals, are not managed as employees or do they necessarily collaborate with other
physicians beyond referral patterns. This differs dramatically from integrated clinical
structures as found at the three institutions interviewed for this dissertation where all the
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physicians are employees. In the culture of Alpha, Beta and Gamma, however,
physicians still function as a community of practice, especially within their
specializations.
Health care providers are atypical organizations because the relationship with
their major agents – physicians functioning within a community of practice -- differs from conventional commercial enterprises.
The literature review section on health care discussed four articles on health care
resistance to change that are relevant to the questions surrounding the implementation of
precision medicine in the existing health care organizational structure. They were:
1. Identifying sources of resistance to change in health care (Landaeta et al 2008);
2. Complexity, leadership, and management in health care organisations (Plesk &
Wilson, 2001);
3. Gaining and maintaining commitment to large-scale change in health care
organizations (Narine & Persaud, 2003);
4. Achieving and sustaining profound institutional change in health care: case study
using neo-institutional theory (Macfarlane et al, 2013).
Landaeta et al 2008, asserts that the introduction of health care technologies has
accelerated the pace of change in the health care environment. A paradigm shift is
analogous. The sources of resistance to change as guideposts for management,
especially in the environment of precision medicine, are useful. The article applied a
phenomenology approach to evaluate 24 known sources of resistance to change in a unit of a hospital. The results suggested that there are sources of resistance to change that are specific only to the health care sector and by extension to precision medicine.
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Sources of resistance to change can be organized in two phases: the stage at
which the change initiative is formulated and the stage at which the change
initiative is implemented as were illustrated previously in Tables 14 and 15 which served as frameworks for the structuring of the interview instrument. The factors in
the Tables were not predictive of stated reasons for resistance to change to
precision medicine the interviews, therefore suggesting incongruity with the
literature on resistance to change in precision medicine. The community of
practice notion is further enforced as the driver.
The second arena for addressing resistance to change in health care is borrowed, as recognized in the literature review, from complexity theory and the relationship to leadership and management in health care organisations (Plesk & Kito,
1999; Plesk & Wilson, 2001). Their conclusions and recommendations must be compared to the findings in the interviews. The articles assert that management views the organization as a machine and believes that considering parts in isolation, specifying changes in detail, battling resistance to change, and reducing variation will lead to better performance. The cultural milieu – the community of practice – of precision medicine as practiced at Alpha, Beta and Gamma belies this position.
The third area regarding health care organizational theory explored
commitment to change in health care. In the article “Gaining and maintaining
commitment to large-scale change in health care organizations” (Narine & Persaud,
2003) the authors build the argument that health care administrators have sought to
improve the quality of health care services by using organizational change as a lever.
The aim of the article was to provide insights into practices that may be utilized to Page 285 | 477
improve the chances of successful change management. In order to effect change, the
authors argue, implementers must first gain commitment to the change through organizational readiness for change. Alpha, Beta and Gamma did not follow this process. The notion of readiness as a function of first deriving consensus and articulating dissatisfaction with the present structure and operations does not hold up in the community of practices that modulate precision medicine. While the authors conclusion
that, “maintaining commitment during the uncertainty associated with the transition
period is imperative. This can be done by successfully managing the transition using
action steps such as consolidating change using feedback mechanisms and making the
change a permanent part of the organization’s culture” (Narine & Persaud, 2003) is
operationally sound but it is mediated by professional exchange and persuasive
evidence. Permanence is a function of the community ultimately embracing the new
paradigm, not the administrative frameworks.
The action items proposed by Narine & Persaud (2003) were used to formulate
an interview strategy for the three institutions. Their provisions advocated consolidating
gains by using feedback mechanisms based on goal-setting theory which indicates that the best performance levels are achieved when specific and difficult (but not impossible) performance goals are set and specific feedback is provided on the attainment of these goals (Locke & Latham, 2002). As stressed in the interviews, the implementation of precision medicine was exploratory and perhaps tentative. The vision or end goal was not a product of consensus building but more a function of program design. In the case of a paradigm shift towards precision medicine, feedback mechanisms within the physician community are imperiled because acting on genetic inputs represents a radical
Page 286 | 477 departure from the status quo and results will be seen over longer periods of time, i.e., often over the lifetime of patients as they progress through the natural history of a disease. Feedback systems, therefore, must follow the rigorous patterns of scientific and clinical exchange. Specifically, precision medicine establishes milestones along the path to full implementation in real time and in response to observations as they occur. The new clinical experimenters frame questions in ways that will satisfy their own requirements for defining success over time.
The fourth article exploring resistance to change in health care focused on achieving and sustaining profound institutional change in health care through a case study using neo-institutional theory (Macfarlane et al, 2013). Institutional Theory was cited in Study 1 when considering the incremental normal science of precision medicine.
In that context, the milieu of paradigm changes invited reconsideration of the framework of relationships among the stakeholders. This dissertation would not be complete without interrogating the processes driving precision medicine against institutional theory. As described previously, institutional theory evaluates the processes by which structures, including schemes, rules, norms, and routines, become established as authoritative guidelines for social behavior (Scott, 2004). Institutional theory explains how these elements are created, diffused, adopted, and adapted over space and time; and how they fall into decline. Given the function of precision medicine within the clinical environment, institutional theory both relates (because it considers dynamic properties) and frustrates (because it appears to rely on authority structures which do not exist in medicine and hospitals the same way as in other organizational settings). Institutional
Page 287 | 477 theory, however, does come closest to accommodating the impact of community of practice in the precision medicine milieu.
Scott et al (2000) further suggest the connection with communities of practice:
“Institutions, defined as social structures that have achieved a high degree of resilience, are influenced by three broad types of social forces or ‘pillars’:
• regulative (laws and contracts which stipulate what must happen),
• normative (assumptions and expectations about what should happen), and
• cultural-cognitive (taken-for-granted scripts and mental models about
what generally does happen) (Scott et al, 2000).”
This interpretation of institutional theory is consistent with the dynamics of communities of practice. Furthermore, institutional logics are socially shared, deeply held assumptions and values that form a framework for reasoning, provide criteria for legitimacy, and help organize time and space (Friedland & Alford, 1991). There is, therefore, some congruity with the implementation of precision medicine with health care organizational theory but only when allowances are made for communities of practice through the lens of Institutional Theory.
Applying communities of practice concepts to precision medicine vis-à-vis theories of resistance to change. Brown & Duguid’s (1991) observation that:
The complex of contradictory forces that put an organization's assumptions and core beliefs in direct conflict with members' working, learning, and innovating arises from a thorough misunderstanding of what working, learning, and innovating are. As a result of such misunderstandings, many modern processes and technologies, particularly those designed to down-skill, threaten the robust working, learning, and innovating communities and practice of the workplace (Brown & Duguid, 1991).
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The emergence of a new paradigm of care, i.e., precision medicine, can be interpreted by the physician community as usurpation of their autonomy and hence a
“down-skilling” of practice. Expanding reliance for diagnostic interpretation to the pathology function, geneticists, and pharmacogenomics pharmacists – whether or not a managerial directive – is a function of dealing with a different guild in the care process.
Mudambi & Swift (2009) address mitigation of this tension between the guilds.
Again, guilds are not communities of practice as defined herein. In the organizational structure, however, of a provider institution advocating precision medicine the roles of guild members and the communities of practice are both comprised largely or exclusively of physicians. In fact, some physicians might simultaneously be a member of a guild that is in conflict with a community of practice to which they also belong. The potential for conflicts abound and – if not directly causal in resistance to precision medicine – are at least significant risk-factors. The prescription offered by Mudambi &
Swift (2009) is that an organization can proactively manage the social and knowledge networks among its participants.
Is the community of practice construct in relation to precision medicine at odds with prevailing resistance theory? There is an opportunity for greater exploration of communities of practice in the resistance literature, as well as the Mudambi & Swift
(2009) findings as causal factors in resistance. The interview data is further suggestive that the community of practice culture and ethos at Alpha, Beta and Gamma are at the very least stronger than found at most other health care providers, perhaps even unique.
If they are the exceptions to the rule, that further reinforces the role of communities of practice in this study’s thesis. Comparative analyses of the community of practice
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cultures and ethos among health care providers at large could be illuminating, especially when probing the interplay of medical specialties and the role of boundary spanners in the promulgation of knowledge and clinical strategies.
Do the Peculiarities of Implementing Precision Medicine Inform the Organizational Literature on Resistance to Change?
The Propositions that emerge from the interviews do not contradict health care organizational theory and the explanations of resistance to change. The theories, however, are not fully predictive or descriptive of the processes that have been employed at Alpha, Beta and Gamma. The theories are robust but are predicated on organizational structures or relationships with employees that do not anticipate the dynamics of the practice of medicine, especially the role of communities of practice among physicians. Although precision medicine is delivered within the context of hospital systems as organizations, as a paradigm shift it provokes change in medical practice and within or among communities of practice. As already established, communities of practice do not function the same way as traditional organizations. What is a “community of practice”?
Again, a community of practice is “a persistent, sustaining social network of individuals who share and develop an overlapping knowledge base, set of beliefs, values, history and experiences focused on a common practice and/or mutual enterprise”
(Barab, 2002).
The transition from viewing medicine as a community that has long been characterized by collegiality and morality to the concept of medicine as a community of practice in which learning takes place has an inherent logic. The cultural, structural, and behavioral aspects of a collegial
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profession as well as its moral base become parts of the norms of practice (Cruess et al 2018).
The self-identification of physicians in communities of practice
supersedes the formal health care provider structure. It is the community that
determines and oversees the standards of practice by which competence is
determined. According to Mann et al (2011) learning is a social rather than an
individual activity and much of it occurs at the unconscious level, resulting in the
accumulation of tacit knowledge. “The learning is ‘situated’ in the community and the content is given authenticity because it is acquired within the same context in which it is applied” (Cruess et al, 2018; Lave, 1991). Given the paradigm shift that precision medicine represents, the community of practice must ultimately embrace and advocate conformity with the principles of clinical implementation, monitoring and adjustment in the face of evidence.
Medicine as a profession, as earlier portrayed, can be characterized by the
three essential elements of a community of practice: domain, community, and
practice. Snyder & Wenger (2010) state that there must be a domain with clear
boundaries creating common ground and common identity. Similarly, they posit
that the presence of a community creates the social fabric within which learning
occurs. Medical specialties constitute strong communities of practice. Finally,
according to Wenger (1998):
Practice refers to the specific knowledge and skills that the community shares and develops, consisting of a set of frameworks, ideas tools, information, styles, language, stories, and documents that the community members share. . . in medicine practice consists of clinical care, educational practices, and research (Wenger, 1998). Page 291 | 477
The self-image of physicians and the community in which they acquire
knowledge and practice medicine is a powerful milieu that transcends their employment
or contractual engagement with any organization. Study 2 asked earlier, “Is the
physician community of practice, therefore, subject to the same forces within
organizations seeking to make changes in systems, policies, practices or standards? Or are there countervailing forces at work?”
This study has demonstrated that physicians are acting or resisting under the primacy of their community of practice and that conventional remedies to resistance to change are not wholly applicable owing to the force of such communities. A community of practice in medicine will respond to evidence suggesting that approaches to prevention, diagnosis, procedure, or therapeutic intervention should be changed, but the individual physician is reacting within the framework of the community of practice – the community which establishes and oversees standards of practice.
When the impetus of change is a straightforward new development or innovation, the community can respond, sometimes with alacrity. On the other hand, when the change affects fundamental clinical decision making, practice patterns, the patient care journey, ways of measuring outcomes or means of rewarding services, the community of practice responds more thoughtfully but slowly. In other words, the changes associated with the paradigm shift of precision medicine are subject to assessment, validation, and consent by the community of practice, thus the management of resistance must be through a paradigm of similar force directed at the collective. In
these ways, the experience of implementing precision medicine provides incongruities
Page 292 | 477 with the body of literature on resistance to change. It informs such theory by introducing the concept of communities of practice and their power to influence or suppress change.
[END OF CHAPTER 3/STUDY 2]
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CHAPTER 4
CONCLUSIONS
Synthesis of Studies 1 and 2: Lessons from the Research
Precision medicine represents one of the few paradigm shifts in medical history meeting the criteria of Thomas Kuhn (1962) as posited in the Structure of Scientific
Revolutions. The pace of absorption of health care technologies has never been predictable. Improvements become standards of practice at a punctuated rate as physicians filter implementation of innovation through loosely defined processes for establishing standards of care even within long-standing paradigms of medical practice.
Innovations merge into practice through evidence based positive outcomes and the missionary zeal of practitioners. When change is defined by a paradigm shift, however, resistance characterizes both professional and institutional response as currently observed in the protracted adoption of precision medicine.
Study 1 explored the commonly postulated reasons for resistance to precision
medicine and expands the research to examine the organizational and professional
response to paradigm shift-associated change. Only a handful of health care providers
have developed fully integrated precision medicine programs despite the broad
availability of precision medicines and associated diagnostics. Furthermore, resistance
cannot be explained by unresolved issues related to regulatory approval, inadequate
public policy measures, or financial reimbursement.
Resistance to precision medicine resides at the level of physicians for whom the paradigm represents reformulation of medical practice and decision making, and at an
Page 294 | 477 organizational level where new systems and relationships are in play. True Kuhnian paradigm shifts are factors in resistance to change meriting further exploration in organizational theory literature.
Precision medicine as a paradigm of care has been evolving for 75 years but implementation has arrived at only a handful of health care providers in the United
States, illustrated herein by Alpha, Beta and Gamma. Challenges to the implementation of precision medicine pose a series of issues. There are foundational concerns related to the antecedent conditions necessary for incorporation into care delivery and guidelines for professional practice. These concerns are further exacerbated by matters of provider readiness regarding operational positioning into patient care relative to the cultures and systems established at the few exemplary institutions. Finally, there are professional resistance to change dynamics regarding the pace of adoption and appropriateness of adoption of the precision medicine paradigm. The research in this study took a
Grounded Theory approach to studying the physician response and organizational dynamics at the three leading precision medicine provider institutions in the United
States.
Through interviews with 50 physicians, scientists, managers, support functionaries and ethicists, 42 Findings and six Propositions were identified as antecedent conditions for a precision medicine program. Within the Findings were embedded many observations that physician resistance was not an individual function but was representative of the community of practice milieu of medicine. Despite the readiness of pharmaceuticals and diagnostics and the urgency for adoption, the clinical establishment of precision medicine is lagging because the organizational antecedents
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for implementation have been insufficiently incorporated into systems planning and
execution across the spectrum of health care providers in the US. Resistance to precision
medicine suggests that processes in the development of standards of practice inform
theories of organizational change particularly related to medical communities of practice.
Limitations of the Study
The Paradigm Shift Argument. The study relies on a historiography of Kuhnian paradigm shifts in the life sciences and medicine, which has been a surprisingly neglected field of scholarship. The handful of investigators that have probed this question posit reservations that what is described herein as the Molecular Paradigm does not conform to the Kuhnian criteria because the Molecular Paradigm does not replace a prior paradigm. Study 1 makes substantial arguments and identifies the history and philosophical basis for prior paradigms but there is not yet a scholarly consensus on these matters. The point, however, is that true Kuhnian paradigm shifts encounter resistance – often epochal – because they convey an epistemological restructuring of knowledge in a field. There is, however, co-existence of the old and new following the few Kuhnian paradigm shifts. The movement towards new normal science, or in this case normal medicine, is a punctuated equilibrium that can distract from the assertion that a paradigm shift is underway. This observation is suggestive of a logical flaw in this dissertation but also provokes an opportunity for further research.
The Inevitability of Precision Medicine Argument. A strong biological, market, and physician behavior set of observations makes a compelling case that precision
Page 296 | 477 medicine has been anticipated in the direction of pharmaceutical development over the last century. A counterargument is that the historic trend towards small molecule specificity falls into a different category of medicinal chemistry than precision medicine.
The point of the argument is that clinical practice has long sought pharmaceuticals that have the most direct effect with the fewest negative consequences and that such a desire establishes a pathway to precision medicine.
The Materiel Readiness of Precision Medicine. While the dissertation provides a compelling inventory of approved precision medicines and related companion diagnostics (materiel), as well as a characterization of these products still in the developmental pipeline, it does not record the actual degree of clinical usage of these products. Such data might be available at significant cost from private vendors and could add depth or challenge the argument that physicians have available the armamentarium to practice precision medicine. Weak adoption of such products could signal weakness in the argument.
Resolution of the Regulatory Oversight of Precision Medicine. Study 1 made the argument that the direction of the regulatory oversight of precision medicine is essentially resolved, albeit proceeding with caution. Most pharmaceutical developers and clinicians would argue the opposite and that the process of regulation is still in its earliest stages. This author concedes that the pace of regulatory review does not move with alacrity but that there is an inventory of approved medicines and companion diagnostics that are enough to drive a movement towards precision medicine.
Resolution of the Economics of Precision Medicine. Similar to regulatory oversight, it is only the direction of economic assessment and reimbursement that is
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resolved, and then only in broad strokes. The interviews, contrary to the assertions in
Study 1, disclosed that reimbursement remains an obstacle towards wider adoption of precision medicine, especially among those physicians who seek to protect the economic welfare of their patients. Furthermore, it can be asserted that precision medicine will exacerbate health inequity between the haves and have nots owing to the cost and pricing structures associated with precision medicine and the health systems human resource and infrastructural investment necessary for its implementation.
Defining Change and Resistance to Change. Study 2 established the history and trends in the literature regarding the definitions of change and the research streams that explore resistance to change. Study 2 also asserts, however, that the literature’s focus is on organizations and groups within organizations, not on communities of practice, such as medicine. The organization of medical practice – whether a physician is an independent practitioner or an employee – is such that organization frameworks and models do not apply. Study 2 argues that there is not strong correspondence between the organization theories of resistance to change and community of practice resistance to change. This is subject to challenge and the theories derived from that assertion may be weakened.
Selection of “True Believing” Institutions and Professionals. Study 2 acknowledges that the 50 professionals interviewed were advocates of precision medicine and could only speculate as to why the majority of colleagues remain either skeptical or unwilling to adopt the principles of practice. The degree of ardor encountered in the interviews was not expected. Study 2 might not fully capture the underlying basis of resistance to precision by the medical community. Future
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investigation should probe resistance among physicians associated with institutions in
the Level One or Two categories of the PMC Landscape study.
Applicability of Grounded Theory to the Research Questions. Grounded Theory
is a complex and difficult qualitative methodology to apply under any research
circumstances. The complexity of the participants and resistance to adoption of precision
medicine challenges the utility of Grounded Theory. A classical hypothetico-deductive
approach – perhaps based on the Propositions herein -- might be more revealing of the
underlying issues and would serve to simplify and focus the questions and interview structure. In defense of this methodology, this study constituted one of the few – perhaps the only – study of the organizational dynamics behind precision medicine and as such can provide a backdrop and structure for future inquiry.
Analysis of the Propositions Derived from Grounded Theory. The Propositions derived from the interview Findings are functional abstracts from the thrusts of the
interviews, but their relevance or argumentative strengths are testable in future research.
Readers may identify other testable Propositions embedded in the full array of 42
Findings.
Opportunities for Additional Research
Numerous opportunities for future research on the implementation of precision
medicine and resistance to change to paradigm shifts in science when applied to the
community of practice that characterizes physician behavior and decision making. By
way of example, the following are offered:
Applicability of Grounded Theory to the study of organizational dynamics in
medical decision making and health care organizations. This study constituted one of Page 299 | 477
the few – perhaps the only – study of the organizational dynamics behind precision
medicine and as such had to provide the basis for future inquiry using a foundational
research methodology.
Further exploration of the role of communities of practice and guilds in
resistance to change. The works of Lave and Wenger (1990) and Brown and Duguid
(1991) appear to be overlooked in their treatment of communities of practice vis-à-vis resistance to change. Furthermore, Mudambi and Swift (2009) offer compelling research opportunities for further testing of their propositions in the nature of guilds and innovation. Both streams of literature are relevant to the implementation of precision medicine but also have broader implications for the study of innovation generally, and absorption of innovation in particular.
A comparative analyses of the community of practice ethos and cultures. As noted above, the community of practice orientations at Alpha, Beta and Gamma may suggest that this is a variable in determining resistance to change and its management in clinical circumstances. If so, further investigation and comparisons are avenues for significant future research in medical decision making and organizational theory.
The structure of life science revolutions. Paradigm shifts in physics and cosmology are based on Copernican cosmology, the Newtonian Revolution, Relativity and Quantum Theory. Using the Kuhnian framework might not be descriptive or predictive of the structure of life science revolutions. Study 1 of this paper established a historiographic approach to the study of paradigm shifts in medicine and the life sciences, but this is elementary relative to the opportunity to a full scale inquiry in examining revolutions in the life sciences that force a re-evaluation of discovery up to
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that point in history, usher in a new epistemology of biology, and influence clinical
practice and decision making.
Precision medicine and global health equity. The complexity associated with the
systems and organizational implementation of precision medicine, in combination with
the impact on medical practice begs the question as to whether and how precision medicine can be incorporated into health care in the developing world. A preliminary view is that precision medicine will exacerbate the differences between the haves and the have nots. How will the required changes be manifest in these two geographic theaters of human need? What are the antecedent conditions in each? Where are the challenges common? Where do they diverge? These important questions related to global health equity are beyond this current inquiry but should be addressed in future research built on this dissertation.
The sample size of institutions. Should the sample size in terms of institutions and interviewees engaged in precision medicine be expanded in future research? While it might perhaps be more compelling to have a dozen or even a handful of similar
institutions across the five levels of adoption described in the PMC Landscape Study,
there would be limited insights gained from all but the Level Five Providers – for
purposes of this dissertation – although future investigation might explore the
organizational dynamics at the other levels with particular attention to inertia and resistance.
Testing the six Propositions of this study. The Propositions were derived from the 42 findings from the interviews. They are stated in such a way that they can be tested
Page 301 | 477 against their implementation at new programs or, ideally, against the practices in place at the Level 3 or Level 4 provider organizations in the PMC Landscape Study (2019).
[END OF CHAPTER 4]
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DOCUMENTATION AND SUPPORTING MATTER
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APPENDIX A IRB Review
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APPENDIX B CURRENTLY APPROVED PRECISION MEDICINES WITH BIOMARKERS
Medicine Name (Brand Name) Biomarker(s) Indication(s) Adjuvant Therapy 1 Cevimeline (Evoxac®) CYP2D6 Dry mouth 2 Rasburicase (Elitek®) G6PD; CYB5R1-4 Hyperuricemia, hemolysis, and methemoglobinemia 3 Sodium phenylacetate and sodium NAGS; CPS1; ASS1; Urea cycle disorders benzoate (Ammonul®) OTC; ASL; ARG 4 Sodium phenylbutyrate (Buphenyl®) CPS1; OTC; ASS1 Urea cycle disorders Analgesia and Anesthesiology 5 Celecoxib (Celebrex®) CYP2C9 Pain 6 Codeine CYP2D6; CYP3A4; Pain UGT2B7 7 Mivacurium (Mivacron®) Cholinesterase gene Anesthesia adjunct 8 Tramadol (Ultram®) CYP2D6 Pain Cardiovascular 9 Carvedilol (Coreg®) CYP2D6 Cardiovascular disease 10 Clopidogrel (Plavix®) CYP2C19 Antiplatelet response 11 Isosorbide and hydralazine (Bidil®) NAT1; NAT2 Heart failure 12 Lomitapide LDLR Familial hypercholesterolemia 13 Metoprolol (Toprol-XL®) CYP2D6 Cardiovascular disease 14 Mipomersen sodium (Kynamro®) LDLR Familial hypercholesterolemia 15 Pravastatin LDR High cholesterol 16 Propafenone (Rythmol SR®) CYP2D6 Cardiac arrhythmia 17 Quinidine CYP2D6 Cardiac arrhythmia, malaria 18 Simvastatin (Zocor®) SLCO1B1 High cholesterol 19 Warfarin (Coumadin®) CYP2C9; VKORC1; Anti-blood clotting, protein C or S stroke prevention deficiencies Endocrinology 20 Glyburide G6PD Diabetes 21 Chlorpropamide G6PD Diabetes 22 Glimepiride G6PD; CYP2C9 Diabetes 23 Glipizide G6PD Diabetes Gastroenterology 24 Dexlansoprazole (Dexilant®) CYP2C19 Heartburn, gastroesophageal reflux disease, and esophageal damage 25 Esomeprazole (Nexium®) CYP2C19 Acid indigestion, peptic ulcer disease, and gastroesophageal reflux disease
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26 Lansoprazole (Prevacid®) CYP2C19 Peptic ulcer disease, gastroesophageal reflux disease 27 PEG-3350, sodium sulfate, sodium chlo- G6PD Laxative ride, potassium chloride, sodium ascorbate, and ascorbic acid (Moviprep®) 28 Rabeprazole (Aciphex®) CYP2C19 Gastroesophageal reflux disease Hematology 29 Eltrombopag (Promacta®) F5; SERPINC1 Thrombocytopenia, aplastic anemia 30 Methylene blue (Provayblue) G6PD Methemoglobinemia Immunology 31 Indacaterol (Arcapta®) UGT1A1 COPD Infectious Disease 32 Abacavir (Ziagen®) HLA-B*57:01 HIV 33 Atazanavir (Reyataz®) UGT1A1 HIV 34 Boceprevir (Victrelis®) IFNL3 Hepatitis C 35 Chloroquine (Aralen®) G6PD Malaria 36 Dapsone G6PD Leprosy 37 Isoniazid (Nydrazid®) NAT1; NAT2 Tuberculosis 38 Mafenide (Sulfamylon®) G6PD Burns 39 Maraviroc (Selzentry®) CCR5 receptor HIV 40 Nitrofurantoin (Furadantin®) G6PD Urinary tract infections 41 Peginterferon alfa-2b (Pegasys®) IL28B Hepatitis B, hepatitis C 42 Primaquine G6PD Malaria 43 Pyrazinamide (Rifater®) NAT1; NAT2 Tuberculosis 44 Quinine sulfate G6PD; CYP2D6; Malaria CYP3A4 45 Rifampin (Rifadin®) NAT1; NAT2 Tuberculosis 46 Sulfamethox-azole and trimethoprim G6PD Bacterial infections (Bactrim®) 47 Telaprevir (Incivek®) IFNL3 Hepatitis C 48 Voriconazole (Vfend®) CYP2C19 Fungal infections Metabolic 49 Allopurinol HLA-B*58:01 High blood uric acid levels, gout Neurology 50 Carbamazepine (Tegretol®) HLA-B*15:02; HLA- Epilepsy, bipolar A*31:01 disorder 51 Carisoprodol (Soma®) CYP2C19 Musculoskeletal pain 52 Clobazam (Onfi®) CYP2C19 Lennox-Gastaut syndrome 53 Dextrometorphan and quinidine CYP2D6 Pseudobulbar affect (Nuedexta®) 54 Divalproex (Depakote®) UCD (NAGS; CPS; Bipolar disorder ASS; OTC; ASL; ARG) (antiepileptic drug) 55 Phenytoin (Dilantin®) HLA-B; CYP2C9 Prevention of seizures Page 347 | 477
56 Tetrabenazine (Xenazine®) CYP2D6 Huntington’s disease 57 Valproic acid (Depakene®) OTC; POLG; NAGS; Epilepsy CPS1; ASS1; ASL; ABL2 58 Vortioxetine (TrintellixTM) CYP2D6 Depression Oncology 59 Ado-trastuzumab emtansine (Kadcyla®) ERBB2 Breast cancer 60 Afatinib (Gilotrif®) EGFR Metastatic non-small cell lung cancer 61 Anastrozole (Arimidex®) ESR1; PGR Breast cancer 62 Arsenic trioxide (Trisenox®) PML-RARA Acute promyelocytic leukemia 63 Busulfan (Busulfex® & Myleran®) BCR-ABL1 Leukemia 64 Bosutinib (Bosulif®) BCR-ABL1 Leukemia 65 Brentuximab vedotin (AdcetrisTM) CD30 Hodgkin’s lymphoma, anaplastic large cell lymphoma 66 Capecitabine (Xeloda®) DPYD Multiple cancers 67 Cetuximab (Erbitux®) EGFR; KRAS Colon cancer 68 Crizotinib (Xalkori®) ALK Lung cancer 69 Dabrafenib (Tafinlar®) BRAF; G6PD Melanoma 70 Dasatinib (Sprycel®) BCR-ABL Leukemia 71 Denileukin diftitox (Ontak®) IL2RA Lymphoma 72 Erlotinib (Tarceva®) EGFR Non-small cell lung cancer 73 Everolimus (Afinitor®) ERBB2; ESR1 Breast cancer 74 Exemestane (Aromasin®) ESR1; PGR Breast cancer 75 5-Fluorouracil (5-FU) (Efudex®) DPYD Multiple cancers 76 Fulvestrant (Faslodex®) ESR1; PGR Breast cancer 77 Gefitinib (Iressa®) EGFR Non-small cell lung cancer 78 Imatinib (Gleevec®) BCR-ABL; PDGFRB; Multiple cancers, KIT; FIP1L1-PDGFRA myelodysplastic syndrome 79 Irinotecan (Camptosar®) UGT1A1 Colon cancer, small cell lung cancer 80 Lapatinib (Tykerb®) ERBB2; HLA-DQA1; Breast cancer HLA-DRB1 81 Lenalidomide (Revlimid®) Del (5q) Multiple myeloma, mantle cell lymphoma, myelodysplastic syndrome 82 Letrozole (Femara®) ESR1; PGR Breast cancer 83 Mercaptopurine (Purinethol®) TPMT Acute lymphocytic leukemia, chronic myeloid leukemia, Crohn's disease, and ulcerative colitis 84 Nilotinib (Tasigna®) UGT1A1; BCR-ABL1 Chronic myelogenous leukemia Page 348 | 477
85 Obinutuzumab (Gazyva®) MS4A1 Chronic lymphocytic leukemia, follicular lymphoma 86 Omacetaxine mepesuccinate (Synribo®) BCR-ABL1 Chronic myeloid leukemia 87 Panitumumab (Vectibix®) EGFR; KRAS Colon cancer 88 Pemetrexed (Alimta®) TS Lung cancer 89 Pertuzumab (Perjeta®) ERBB2 Breast cancer Platinum Therapies 90 Carboplatin ERCC1 Ovarian cancer 91 Cisplatin TPMT Multiple cancers 92 Oxaliplatin ERCC1 Colorectal cancer 93 Nedaplatin ERCC1 Multiple cancers 94 Triplatin tetranitrate ERCC1 Multiple cancers 95 Satraplatin ERCC1 Multiple cancers 96 Ponatinib (Iclusig®) BCR-ABL1 Chronic lymphocytic leukemia, acute lymphocytic leukemia 97 Rituximab (Rituxan®) MS4A1 Non-Hodgkin’s lymphoma, chronic lymphocytic leukemia, and autoimmune diseases 98 Tamoxifen (Nolvadex®) ESR1; ESR2; PGR; F5; Breast cancer F2; CYP2D6 99 Thioguanine (Tabloid®) TPMT Acute myeloid leukemia, acute lymphocytic leukemia, and chronic myeloid leukemia 100 Tositumomab (Bexxar®) MS4A1 Non-Hodgkin’s lymphoma 101 Trametinib (Mekinist®) BRAF Melanoma 102 Trastuzumab (Herceptin®) ERBB2 Breast cancer 103 Tretinoin (Vesanoid®) PML / RARɑ Acute promyelocytic leukemia 104 Vemurafenib (ZelborafTM) BRAF; NRAS Melanoma Psychiatry 105 Aripiprazole (Abilify®) CYP2D6 Schizophrenia, bipolar disorder 106 Amitriptyline (Elavil®) CYP2D6; CYP2C19 Depression 107 Atomoxetine (Strattera®) CYP2D6 ADHD 108 Citalopram (Celexa®) CYP2C19 Depression 109 Clomipramine (Anafranil®) CYP2D6 Depression 110 Clozapine (Clozaril®) CYP2D6 Schizophrenia 111 Desipramine (Norpramin®) CYP2D6 Depression 112 Doxepin (Silenor®) CYP2D6; CYP2C19 Insomnia, depression 113 Fluoxetine (Prozac®) CYP2D6 Depression 114 Fluvoxamine (Luvox CR®) CYP2D6 Obsessive compulsive disorders
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115 Iloperidone (Fanapt®) CYP2D6 Schizophrenia 116 Imipramine (Tofranil-PM®) CYP2D6; CYP2C19 Depression 117 Nortriptyline (Pamelor®) CYP2D6 Depression 118 Paroxetine (Pexeva®) CYP2D6 Major depressive disorder, obsessive compulsive disorder, panic disorder, and generalized anxiety disorder 119 Perphenazine (Trilafon®) CYP2D6 Schizophrenia 120 Pimozide (Orap®) CYP2D6 Tourette’s syndrome Source: Personalized medicines were identified from the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling, accessed June 18, 2019 at https://www.fda.gov/drugs/science-research- drugs/table-pharmacogenomic-biomarkers-drug-labeling
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APPENDIX C COMPENDIUM OF DIAGNOSTICS IN DEVELOPMENT
Appendix C: Compendium of diagnostics in development Generic Drug Drug Names with Status Indication Therapeutic Class Name Companion DX 177Lu-PSMA- 177LU PSMA-R2, Active Diagnosis, Companion SR6, companion companion diagnostic cancer diagnostic diagnostic Anticancer, other abacavir sulfate, 1592, companion Widely Diagnosis, Companion companion diagnostic Launched infection diagnostic diagnostic Antiviral, anti-HIV ADHD therapy, ADHD therapy, Active Diagnosis, Companion companion companion diagnostic CNS diagnostic diagnostic, Psychostimulant AlkaliDx albumin ACDx; LADR 10, Active Diagnosis, Companion companion companion diagnostic cancer diagnostic diagnostic, Centurion BioPharma alectinib, Alecensa, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other altiratinib, DCC-2701, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other alvocidib, HMR-1275, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other AML MRD AML MRD assay; SLS- Active Diagnosis, Companion assay 001, companion cancer diagnostic diagnostic Anticancer, vaccine Anticancer, immunological anifrolumab, MDX-1333, companion Active Diagnosis, Companion companion diagnostic unspecified diagnostic diagnostic, Immunosuppressant Medimmune anti-B7-H4 FPA 150, companion Active Diagnosis, Companion antibody, diagnostic cancer diagnostic companion Anticancer, diagnostic, Five immunological Prime Therapeutics anticancer, anticancer, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic, 2X Anticancer, other Oncology anticancer, anticancer, companion Ceased Diagnosis, Companion companion diagnostic, Eli Lilly; cancer diagnostic diagnostic, anticancer, companion Anticancer, other Qiagen-1 diagnostic, Qiagen-1
Page 351 | 477 aramchol, aramchol, companion Active Diagnosis, Companion companion diagnostic hepatic diagnostic diagnostic Hepatoprotective ASP-0113, ASP-0113, companion Active Diagnosis, Companion companion diagnostic infection diagnostic diagnostic, Therapeutic vaccine, Abbott anti-infective AZD-9291, AZD-9291, companion Active Diagnosis, Companion companion diagnostic cancer diagnosticAnticancer, diagnostic other BDX-001 BDX-001; BDX001; GI- Active Diagnosis, Companion 4000, companion cancer diagnostic diagnostic Anticancer, other bemarituzumab, FPA 144, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, immunological BGB-324, BGB-324, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other BLU-285, BLU 285, companion Active Diagnosis, Companion companion diagnostic diagnostic, cancer diagnostic diagnostic, Blueprint Medicines Anticancer, other Blueprint Medicines BLU-554, BLU 554, companion Active Cancer, Companion companion diagnostic Medicines, unspecified diagnostic diagnostic companion diagnostic Anticancer, other Bond Oracle APT-101, companion Widely Diagnosis, Companion Her2 IHC diagnostic trastuzumab, Launched cancer diagnostic System companion diagnostic, Anticancer, other Leica Biosystems BRACAnalysis ABT-888, companion Active Diagnosis, Companion diagnostic companion cancer diagnostic diagnostic Anticancer, other BRAF V600, 1120212, companion Active Diagnosis, Companion companion diagnostic; trametinib, cancer diagnostic diagnostic companion diagnostic Anticancer, other BRAF V600, BRAF V600, companion Widely Diagnosis, Companion companion diagnostic Launched cancer diagnostic diagnostic, Anticancer, other Roche brentuximab Adcetris, companion Active Diagnosis, Companion vedotin, diagnostic cancer diagnostic companion Anticancer, diagnostic immunological BriaVax, BriaDx; BriaVax, Active Diagnosis, Companion companion companion diagnostic cancer diagnostic diagnostic Anticancer, other bucindolol Bextra, Incara, Active Diagnosis, Companion hydrochloride, companion diagnostic coronary diagnostic companion Vasodilator, coronary diagnostic Cardiovascular Antiarrhythmic
Page 352 | 477 c-Met, ARQ-197, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other CardiAMP CardiAMP therapy; Active Diagnosis, Companion therapy cardiovascular therapy, coronary diagnostic BioCardia, companion Cardiovascular diagnostic CB-103, CB-103, companion Active Diagnosis, Companion companion diagnostic; CB103, cancer diagnostic diagnostic companion diagnostic Anticancer, other CBL-0137, CBL 0137, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic cetuximab, BMS-564717, companion Ceased Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other claudiximab, Claudetect 18.2; Widely Diagnosis, Companion companion claudiximab, companion Launched cancer diagnostic diagnostic diagnostic Anticancer, other CMB-305, CMB-305, companion Active Diagnosis, Companion companion diagnostic; CMB305, cancer diagnostic diagnostic companion diagnostic Anticancer, vaccine cobitolimod, DIMS 0150, companion Active Diagnosis, Companion companion diagnostic inflammation diagnostic diagnostic Anti-inflammatory crizotinib, ROS1 gene fusions Active Diagnosis, Companion companion detection kit cancer diagnostic diagnostic, Anticancer, other Amoy crizotinib, ALK IHC rabbit Active Diagnosis, Companion companion monoclonal primary cancer diagnostic diagnostic, antibody assay Anticancer, other Roche CXD-101, CXD-101, companion Active Diagnosis, Companion companion diagnostic; CXD101, cancer diagnostic diagnostic companion diagnostic Anticancer, other c-Met, ARQ-197, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other defactinib, PF 04554878, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other deferasirox, Exjade FCT, companion Widely Diagnosis, Companion companion diagnostic Launched blood diagnostic diagnostic Metabolic and enzyme disorders E-7438, E-7438, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other EGFR, AVL-301, companion Widely Diagnosis, Companion companion diagnostic, Qiagen Launched cancer diagnostic diagnostic, Anticancer, other Qiagen
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Elecsys AMH Elecsys AMH; FE Active Diagnosis, Companion 999049, companion gynaecology diagnostic diagnostic Fertility enhancer enoblituzumab, MGA-271, companion Active Diagnosis, Companion companion diagnostic; MGA271, cancer diagnostic diagnostic companion diagnostic; Anticancer, other enoblituzumab, companion diagnostic ensituximab, NEO 101, companion Active Diagnosis, Companion companion diagnostic, Neogenix cancer diagnostic diagnostic Anticancer, other entrectinib, NMS-E628, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other enzalutamide, enzalutamide, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other epidermal growth ABX-EGF, companion Widely Diagnosis, Companion factor receptor, diagnostic Launched cancer diagnostic companion Anticancer, other diagnostic EPZ-01, EPZ-004777, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other erismodegib, LDE-225, companion Widely Diagnosis, Companion companion diagnostic Launched cancer diagnostic diagnostic Anticancer, other erlotinib, CP-358774, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other Escherichia coli Escherichia coli MAb Active Diagnosis, Companion MAb therapy, therapy, Arsanis, infection diagnostic Arsanis, companion diagnostic Antibacterial, other companion diagnostic farletuzumab, MORAb-003, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other FF-284, CH-5183284, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other FSM-26, FSM-26, companion Active Diagnosis, Companion companion diagnostic respiratory diagnostic diagnostic Respiratory FST-12, FST-12, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other gallium (68Ga)- 177-Lu-DOTA- Active Diagnosis, Companion edotreotide octreotate, companion cancer diagnostic diagnostic Anticancer, hormonal gantenerumab, R-04909832, companion Active Diagnosis, Companion companion diagnostic, Roche CNS diagnostic diagnostic, Cognition enhancer Roche
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GC-33, GC-33, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, immunological gefitinib, EGFR RGQ Plasma PCR Widely Diagnosis, Companion companion diagnostic, Qiagen-2 Launched cancer diagnostic diagnostic, Anticancer, other Qiagen-2 glesatinib, MGCD-265, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other glesatinib, MGCD265, companion Active Diagnosis, Companion companion diagnostic, Foundation cancer diagnostic diagnostic, Medicine Anticancer, other Foundation Medicine glesatinib, glesatinib, companion Active Diagnosis, Companion companion diagnostic, Qiagen cancer diagnostic diagnostic, Anticancer, other Qiagen HBsAg, Cylatron, companion Widely Diagnosis, Companion companion diagnostic Launched infection diagnostic diagnostic Antiviral, other HER2, DakoCytomation Her2 Widely Diagnosis, Companion companion FISH pharmDx Kit Launched cancer diagnostic diagnostic, Dako Anticancer, other 1 HER2, HER2, companion Widely Diagnosis, Companion companion diagnostic, Dako 2 Launched cancer diagnostic diagnostic, Dako Anticancer, other 2 Herceptin + Herceptin + lapatinib, Ceased Diagnosis, Companion lapatinib, companion diagnostic, cancer diagnostic companion GlaxoSmithKline Cancer, breast Anticancer, other diagnostic, Hoffmann-La Roche HIV vaccine, AIDS vaccine, Active Diagnosis, Companion companion companion diagnostic, infection diagnostic diagnostic, Diaxonhit Diaxonhit ibandronic acid, BM-210955, companion Active Diagnosis, Companion companion diagnostic unspecified diagnostic diagnostic Osteoporosis treatment IBD-110 IBD-110; IBD110 Active Diagnosis, GI Companion diagnostic IBD-210 EP-8018, companion Active Diagnosis, GI Companion diagnostic diagnostic GI inflammatory/bowel disorders ibrutinib, PCI-32765, companion Widely Diagnosis, Companion companion diagnostic Launched cancer diagnostic diagnostic Anticancer, other Page 355 | 477
IMAB-027, GT-512, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other imatinib CGP-57148B, companion Widely Diagnosis, Companion mesilate, diagnostic Launched cancer diagnostic companion Anticancer, other diagnostic, Dako imatinib CGP-57148B, companion Widely Diagnosis, Companion mesilate, diagnostic, Ventana Launched cancer diagnostic companion Anticancer, other diagnostic, Ventana imgatuzumab, GA-201, companion Ceased Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other immunology immunology disorders, Ceased Diagnosis, Companion disorders, UCB, UCB, companion unspecified diagnostic companion diagnostic Immunological, diagnostic unspecified IMO-8400, IMO 8400, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other irinotecan, CPT-11, nanoliposomal, Active Diagnosis, Companion Merrimack, companion diagnostic cancer diagnostic companion Anticancer, other diagnostic istiratumab, MM-141, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other IT-139, IT-139, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other JNJ-64290694, JNJ-64290694, Active Diagnosis, Companion companion companion diagnostic cancer diagnostic diagnostic Anticancer, other JNJ-64413739 18F-JNJ-64413739 Active Diagnosis, Companion CNS diagnostic Imaging agent K-RAS Mutation ABX-EGF, companion Widely Diagnosis, Companion Kit diagnostic, Qiagen Launched cancer diagnostic Anticancer, other Keytruda, Keytruda, companion Active Diagnosis, Companion companion diagnostic, Nanostring cancer diagnostic diagnostic, Technologies Anticancer, other Nanostring Technologies Klebsiella Klebsiella pneumoniae Active Diagnosis, Companion pneumoniae MAb therapy, Arsanis, infection diagnostic MAb therapy, companion diagnostic Antibacterial, other Arsanis, companion diagnostic lampalizumab, lampalizumab, Active Diagnosis, Companion companion companion diagnostic ocular diagnostic diagnostic Page 356 | 477
Ophthalmological, other lapatinib GW-2016, companion Widely Diagnosis, Companion ditosylate, diagnostic Launched cancer diagnostic companion Anticancer, other diagnostic larotrectinib, IHC pan-TRK assay; Active Diagnosis, Companion companion LOXO-101, companion cancer diagnostic diagnostic diagnostic Anticancer, other lenalidomide, CC 5013, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other LOR-253, APTO 253, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other LOXO-292, LOXO-292, Companion Active Diagnosis, Companion Companion diagnostic cancer diagnostic diagnostic Anticancer, other lumretuzumab, RG-7116, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other LY-2875358, LA-480, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, immunological MAN-01, MAN-01, companion Active Diagnosis, Companion companion diagnostic, Q BioMed ocular diagnostic diagnostic, Q Ophthalmological, BioMed antiglaucoma MEDI-3902, MEDI-3902, companion Active Diagnosis, Companion companion diagnostic infection diagnostic diagnostic Immunomodulator, anti-infective MEDI-4893, MEDI-4893, companion Active Diagnosis, Companion companion diagnostic infection diagnostic diagnostic Immunomodulator, anti-infective microbiome, microbiome, companion Active Diagnosis, Companion companion diagnostic, Biotagenics inflammation diagnostic diagnostic, GI Biotagenics inflammatory/bowel disorders midostaurin, CGP 41251, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other MK-4827 + Keytruda + MK-4827, Active Diagnosis, Companion Keytruda, companion diagnostic, cancer diagnostic companion Merck Anticancer, other diagnostic, Myriad Genetics MK-8931, MK-8931, companion Active Diagnosis, Companion companion diagnostic, Luminex, CNS diagnostic diagnostic, Merck & Co Cognition enhancer Luminex
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MM-151, MM-151, companion Active Diagnosis, Companion companion diagnostic; MM151, cancer diagnostic diagnostic companion diagnostic Anticancer, other mogamulizumab, AMG-761, companion Widely Diagnosis, Companion companion diagnostic, Kyowa Hakko Launched cancer diagnostic diagnostic, Kirin Anticancer, other Kyowa Hakko Kirin monoclonal monoclonal antibodies, Active Diagnosis, Companion antibodies, companion diagnostic kit, unspecified diagnostic companion Shenogen Anticancer, other diagnostic kit, Shenogen MS-001c, MS-001c, companion Active Diagnosis, Companion companion diagnostic, cancer diagnostic diagnostic, METABOSTEM Anticancer, other METABOSTEM MS-27-275, MS-27-275, companion Active Diagnosis, Companion companion diagnostic, Syndax cancer diagnostic diagnostic, Anticancer, other Syndax MSB-2311, MSB 2311, companion Active Diagnosis, Companion companion diagnostic, Mabspace cancer diagnostic diagnostic, Biosciences Mabspace Biosciences navitoclax, A-855071.0, companion Active Diagnosis, Companion companion diagnostic navitoclax, cancer diagnostic diagnostic companion diagnostic Anticancer, other Nexvax 2, Nexvax 2, companion Active Diagnosis, Companion companion diagnostic inflammation diagnostic diagnostic Anti-inflammatory nilotinib, AMN-107, companion Widely Diagnosis, Companion companion diagnostic Launched cancer diagnostic diagnostic Anticancer, other nilotinib, Tasigna, companion Active Diagnosis, Companion companion diagnostic, MolecularMD cancer diagnostic diagnostic, Anticancer, other MolecularMD niraparib, myChoice HRD; Active Diagnosis, Companion companion niraparib, companion cancer diagnostic diagnostic, diagnostic, Myriad Anticancer, other Myriad Genetics Genetics nivolumab, BMS-936558, companion Widely Diagnosis, Companion companion diagnostic, Dako Launched cancer diagnostic diagnostic, Dako Anticancer, other NMI-300, NMI-300, companion Active Diagnosis, Companion companion diagnostic; NMI300, cancer diagnostic diagnostic companion diagnostic Anticancer, other NMI-500, NMI-500, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other NS-0200, NS-0200, companion Active Diagnosis, Companion companion diagnostic hepatic diagnostic diagnostic Hepatoprotective Page 358 | 477
NVX-108, GliomaSTRAT, RiboMed Active Diagnosis, Companion companion cancer diagnostic diagnostic Anticancer, other olaparib, AZD-2281, companion Active Diagnosis, Companion companion diagnostic, Foundation cancer diagnostic diagnostic, Medicine Anticancer, other Foundation Medicine panitumumab, MiSeqDx kit Widely Diagnosis, Companion companion Launched cancer diagnostic diagnostic, Anticancer, other Amgen PC-MAb, CVDefine kit; PC-MAb, Active Diagnosis, Companion companion companion diagnostic, coronary diagnostic diagnostic, Athera Biotechnologies Cardiovascular Athera Biotechnologies PEG IFN alpha- CAP/CTM HCV 2.0; Widely Diagnosis, Companion 2a, companion PEG IFN alpha-2a, Launched infection diagnostic diagnostic-2 companion diagnostic-2 Antiviral, other peginterferon PEG IFN alpha-2a, Widely Diagnosis, Companion alfa-2a, companion diagnostic Launched infection diagnostic companion Antiviral, other diagnostic PEGPH20, PEGPH-20, companion Active Diagnosis, Companion companion diagnostic, Halozyme cancer diagnostic diagnostic, Anticancer, other Halozyme pembrolizumab, Keytruda, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other pembrolizumab, Keytruda, companion Active Diagnosis, Companion companion diagnostic, Foundation cancer diagnostic diagnostic, Medicine Foundation Medicine pemigatinib, INCB 54828, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other PolyPEPI, PolyPEPI 1, companion Active Diagnosis, Companion companion diagnostic; ovarian cancer cancer diagnostic diagnostic vaccine, Treos Bio Anticancer, other pomaglumetad LY-2140023, companion Active Diagnosis, Companion methionil, diagnostic, Denovo unspecified diagnostic companion Biopharma Neurological diagnostic, Denovo Biopharma ponatinib, AP-24534, companion Ceased Diagnosis, Companion companion diagnostic, MolecularMD cancer diagnostic diagnostic, Anticancer, other MolecularMD PTI-125DX, PTI 125DX, companion Active Diagnosis, Companion companion diagnostic CNS diagnostic diagnostic Cognition enhancer Page 359 | 477
PTX-100, GGTI-2418, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other PU-AD-PET, PU-AD-PET, companion Active Diagnosis, Companion companion diagnostic, Samus CNS diagnostic diagnostic, Diagnosis, Neuroprotective Samus cancer Anticancer, other PU-CYT, PU-CYT, companion Active Diagnosis, Companion companion diagnostic, Samus cancer diagnostic diagnostic, Diagnosis, Anticancer, other Samus CNS Neurological PU-H71-PET, 124I-PU-H71; PU-H71- Active Diagnosis, Companion companion PET, companion cancer diagnostic diagnostic, diagnostic, Samus Anticancer, other Samus QBECO, QBECO SSI, companion Active Diagnosis, Companion companion diagnostic inflammation diagnostic diagnostic GI inflammatory/bowel disorders quizartinib AC-220, companion Active Diagnosis, Companion dihydrochloride, diagnostic cancer diagnostic companion Anticancer, other diagnostic Re-188 P2045, BAY86-5284, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, hormonal RG-7304, CK-I27, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other RG-7388, RG 7388, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other RG-7440, GDC 0068, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other RG-7597, MEHD-7945A, Active Diagnosis, Companion companion companion diagnostic cancer diagnostic diagnostic Anticancer, immunological RG-7601, ABT-199, companion Active Diagnosis, Companion companion diagnostic companion cancer diagnostic diagnostic diagnostic Anticancer, other RHB-104, Myoconda, companion Active Diagnosis, Companion companion diagnostic infection diagnostic diagnostic Antimycobacterial rilotumumab, AMG 102, companion Ceased Diagnosis, Companion companion diagnostic, Amgen cancer diagnostic diagnostic, Anticancer, other Amgen rucaparib, AG-14699, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other
Page 360 | 477 rucaparib, CDxBRCA, companion Active Diagnosis, Companion companion diagnostic, Foundation cancer diagnostic diagnostic, Medicine Anticancer, other Foundation Medicine Ruga-S6, AXL receptor tyrosine Active Diagnosis, Companion companion kinase, companion cancer diagnostic diagnostic diagnostic; GA- Anticancer, other S6,companion diagnostic seribantumab, MM-121, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, immunological solithromycin, CEM-101, companion Active Diagnosis, Companion companion diagnostic, Cempra infection diagnostic diagnostic, Anti-infective, other Curetis SP263, MEDI 4736, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, other talazoparib, talazoparib, companion Active Diagnosis, Companion companion diagnostic, BioMarin cancer diagnostic diagnostic, Anticancer, other Myriad Genetics tamoxifen, Ceadan, companion Widely Diagnosis, Companion companion diagnostic Launched cancer diagnostic diagnostic Anticancer, other tavokinogene DNA IL-12, OncoSec Active Diagnosis, Companion telsaplasmid, Medical, companion cancer diagnostic companion diagnostic Anticancer, other diagnostic TG-4010, MUC-1-IL-2, companion Active Diagnosis, Companion companion diagnostic, Beckman cancer diagnostic diagnostic, Coulter Anticancer, other Beckman Coulter TG-4010, MUC-1-IL-2, companion Active Diagnosis, Companion companion diagnostic, Hoffmann-La cancer diagnostic diagnostic, Roche Anticancer, other Hoffmann-La Roche tralokinumab, CAT-354, companion Active Diagnosis, Companion companion diagnostic respiratory diagnostic diagnostic Antiasthma trastuzumab, HER-2 DNA Probe test, Widely Diagnosis, Companion companion AbbVie Launched cancer diagnostic diagnostic, Anticancer, other AbbVie trastuzumab, Herceptin, companion Widely Diagnosis, Companion companion diagnostic, BioGenex Launched cancer diagnostic diagnostic, Anticancer, other BioGenex trastuzumab, HER2 CISH pharmDx Widely Diagnosis, Companion companion Kit, companion Launched cancer diagnostic diagnostic, diagnostic, Dako-2 Anticancer, other Dako-2 Page 361 | 477 trastuzumab, Herceptin, companion Widely Diagnosis, Companion companion diagnostic, Hoffmann-La Launched cancer diagnostic diagnostic, Roche Anticancer, other Hoffmann-La Roche trastuzumab, Herceptin, companion Widely Diagnosis, Companion companion diagnostic, Hoffmann-La Launched cancer diagnostic diagnostic, Roche 1 Anticancer, other Hoffmann-La Roche 1 trastuzumab, Herceptin, companion Widely Diagnosis, Companion companion diagnostic, Life Launched cancer diagnostic diagnostic, Life Technologies Anticancer, other Technologies VAL 201, VAL 201, companion Active Diagnosis, Companion companion diagnostic cancer diagnostic diagnostic Anticancer, hormonal valganciclovir, RG-1227, companion Widely Diagnosis, Companion companion diagnostic Launched infection diagnostic diagnostic Antiviral, other veliparib, veliparib, companion Active Diagnosis, Companion companion diagnostic, AbbVie cancer diagnostic diagnostic, Anticancer, other Myriad Genetics VeriStrat, AV-299, companion Active Diagnosis, Companion companion diagnostic, Biodesix cancer diagnostic diagnostic Anticancer, other Vysis ALK LDK-378, companion Widely Diagnosis, Companion Break Apart diagnostic Launched cancer diagnostic FISH Probe Kit, Anticancer, other AbbVie W-0101, W 0101, companion Active Diagnosis, Companion companion diagnostic, Pierre Fabre cancer diagnostic diagnostic, Pierre Fabre Source: Original compilation by author from US-FDA website and Citeline/PharmaProjects, 2019
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APPENDIX D GLOBAL DEVELOPMENT PIPELINE OF PRECISION MEDICINES AND COMPANION DIAGNOSTICS
Generic Drug Names Summary Development Drug Disease/ Drug Disease Status Drug Name Status Indication
177Lu- 177LU PSMA- 177LU PSMA-R2 (177Lu- Active Cancer, prostate Phase II Clinical PSMA-SR6 R2; 177Lu- PSMA-SR6) is a Trial PSMA-R2; radiotherapeutic, under 177Lu-PSMA- development by Novartis for SR6 the treatment of prostate cancer abacavir 1592; 1592U89; Abacavir sulfate (1592U89) is Widely Infection, Launched sulfate 1592U89 an HIV reverse transcriptase Launched HIV/AIDS succinate; inhibitor, originally developed Ziagen by GlaxoSmithKline (GSK) and now marketed by ViiV Health care (GlaxoSmithKline-Pfizer joint-venture) ADHD ADHD therapy, AlkaliDx is developing a Active Attention deficit Preclinical therapy, AlkaliDx therapy for Attention Deficit hyperactivity AlkaliDx Hyperactivity Disorder disorder (ADHD) as an alternative benign therapy for whom the anesthetic lidocaine does not work, that enables patients to reduce the stimulant dose, or do without them entirely alectinib AF-802; AF802; AF-802/CH-5424802 is an Active Cancer, lung, non- Launched hydrochlori Alecensa; anaplastic lymphoma kinase small cell de alectinib; (ALK) inhibitor, developed by alectinib Chugai for the treatment of hydrochloride nsclc alvocidib DSP 2033; Alvocidib is a semisynthetic Active Solid and liquid Phase II and pre- alvocidib; flavone selective CDK9 tumors of various clinical by indication alvocidib inhibitor, under development by types hydrochloride; Tolero Pharmaceuticals flavopiridol treatment of acute myeloid leukemia (AML).
Aravive-S6 AVB-500; Aravive-S6 (Ruga-S6) is a Active Cancer, Phase I AVB-S6-500; GAS6-AXL signaling pathway unspecified Preclinical AVB500; inhibitor, under development by leukaemia, renal depending on AVBS6500; Aravive Biologics (previously Infection, Zika indication Aravive-S6; Ruga Corporation) for the virus treatment of acute myeloid lymphoma (AML) and certain solid tumour indications including ovarian, pancreatic, renal and breast cancers.
ASN-200 ASN-200; ASN-200 is a fully human Mab, Active Infection, Preclinical ASN200; under development by Arsanis Escherichia coli Preclinical Escherichia coli for the prophylaxis and Infection, Mab therapy, treatment of infections due to Arsanis nosocomial Escherichia coli. ASN-300 ASN-300; ASN-300 is a fully human Mab Active Infection, PreclinicalPreclinical ASN300; therapy, under development by KlebsiellaInfectio Preclinical Klebsiella Arsanis for the prophylaxis and n, , pneumonia, pneumoniae treatment of infections due to hospital-acquired Mab therapy, noscomial Klebsiella Arsanis pneumoniae
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asunercept APG-101; Asunercept (Apocept) is a Active Cancer, brain Status by indication APG101; human, soluble fusion protein Myelodysplastic ranging from Apocept; CAN- comprising the extracellular syndrome Preclinical to Phase 008; CAN008; domain of the CD95 receptor Graft-versus-host II asunercept; and the Fc portion of IgG, disease stroke therapy, under development by Sepsis Apogenix Apogenix for the treatment of Infarction, acute graft-vs-host disease myocardial (aGvHD), and for glioblastoma Ischaemia, multiforme (GBM). cerebral
atezolizuma MPDL-3280A; Genentech has developed Active Solid and liquid Status by indication b MPDL3280A; atezolizumab, an anti-PDL1 tumors of various ranging from RG 7446; RG- human Mab for the treatment of types Preclinical to Phase 7446; RG7446; cancer III; some launched RG7746; RO- 5541267; RO5541267; Tecentriq; atezolizumab
avelumab Bavencio; Avelumab (MSB-0010718C) is Active Solid and liquid Status by indication MSB- an Mab against PD-L1 tumors of various ranging from 0010718C; (programmed cell death ligand), types Preclinical to Phase MSB0010718C; developed by EMD Serono III; some launched PF 06834635; (Merck KgaA) for the treatment PF-06834635; of solid tumours anti PD-L1, Merck KgaA; avelumab AZD-9468 AZD 9468; AZD-9468 (CXD-101) is a Active Solid and liquid Status by indication AZD-9468; histone deacetylase inhibitor, tumors of various ranging from AZD9468; CXD under development by Celleron types Preclinical to Phase 101; CXD-101; for the treatment of solid II CXD101 tumours, colorectal cancer and haematological malignancies.
b-vedotin Adcetris; SGN- Brentuximab vedotin (SGN-35) Active Solid and liquid Status by indication 35; SGN35; b- is an antibody-linked drug tumors of various ranging from vedotin; conjugate (ADC), developed by types Preclinical to Phase brentuximab Seattle Genetics for the III vedotin treatment of haematologic malignancies, including Hodgkin’s lymphoma (HD) and some types of non-Hodgkin’s lymphoma (NHL) expressing CD30, such as anaplastic large cell lymphoma (ALCL). bemarituzu FPA 144; FPA- Bemarituzumab is a humanized Active Solid and liquid Status by indication mab 144; FPA144; monoclonal antibody against a tumors of various ranging from bemarituzumab splice form of fibroblast growth types Preclinical to Phase factor receptor 2b (FGFR2), III under development by Five Prime Therapeutics for the treatment of cancer.
bemcentinib BGB 324; Bemcentinib (BGB-324; R- Active Solid and liquid Status by indication BGB-324; 428) is an orally bioavailable, tumors of various ranging from BGB324; R small-molecule AXL inhibitor, types Preclinical to Phase 428; R-428; under development by II R428; BerGenBio for the treatment of bemcentinib haematological and solid cancer. Page 364 | 477 binimetinib ARRY-162; Binimetinib is a MEK inhibitor, Active Solid and liquid Status by indication ARRY-438162; developed by Array BioPharma tumors of various ranging from ARRY162; for the reduction of types Preclinical to ARRY438162; hypertrophic cardiomyopathy in registration MEK-162; patients with Noonan MEK162; syndrome, melanoma, ovarian, Mektovi; ONO fallopian tube, peritonial, 7703; ONO- colorectal, pancreatic, 7703; oseophageal, thyroid, binimetinib haematological, biliary and non-small cell lung cancers. BLU-554 BLU 554; BLU- BLU-554 is a selective, potent, Active Cancer, liver Phase I Clinical Trial 554; BLU554; irreversible fibroblast growth Cancer, biliary No Development CS 3008; CS- factor receptor 4 (FGFR4) Reported 3008; CS3008; inhibitor, under development by FGFR4 Blueprint Medicines for the inhibitors, treatment of advanced Blueprint hepatocellular carcinoma Medicines (HCC). brain cancer PolyPEPI; PolyPEPI-1112 is an Active Cancer, brain Preclinical vaccine, PolyPEPI 1112; immunotherapy vaccine, under Treos Bio PolyPEPI-1112; development by Treos Bio PolyPEPI1112; using its cancer vaccine brain cancer technology for the treatment of vaccine, Treos glioma. Bio breast Bria-IMT; Bria-IMT is a whole-cell Active Cancer, breast Phase II Clinical cancer BriaVax; SV- vaccine and T helper cell Trial vaccine, BR-1-GM; SV- stimulant, under development BriaCell BR1-GM; breast by BriaCell Therapeutics using cancer vaccine, its cancer immunotherapy BriaCell technology for advanced breast cancer. The whole-cell vaccine is derived from one of the breast cancer patients and the cells are genetically engineered to synthesize and release GM- CSF precisely at the site of vaccine injection which boosts tumour-specific immunity. bucindolol Bextra, Incara; Bucindolol is a long-acting Active Fibrillation, atrial Phase III Clinical Gencaro; MJ- non-selective ß-blocker with Heart failure Trial 13105-1; mild vasodilatory activity, Suspended bucindolol; under development by ARCA bucindolol HCl biopharma for the treatment of chronic heart failure (CHF).
CB-103 CB-103; CB103 CB-103 is a lead first-in-class Active Cancer, Status by indication oral pan-NOTCH inhibitor, unspecified ranging from under development by Cellestia Preclinical to Phase Biotech for the treatment of III; some launched cancer including leukaemia, lymphoma and solid tumours
CBLC-137 CBL 0137; CBLC-137 is an orally Active Cancer, solid, Phase I Clinical Trial CBL-0137; administered next-generation unspecified Phase I Clinical Trial CBL-0137 (IV) curaxin, under development by Cancer, Cleveland BioLabs for the lymphoma, treatment of cancer. It activates unspecified p53 and inhibits NFkB
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cetuximab BMS-564717; Cetuximab (C225) is a Active Various solid C225; EMR- chimaeric Mab specific for tumors 62202; Erbitux; epidermal growth factor IMC-C225 receptor (EGFR), developed by ImClone Systems (Lilly) for cancers overexpressing EGFR. A companion diagnostic has been developed to identify epidermal growth factor receptor (EGFR) expression in normal and neoplatic tissues in colorectal cancer patients. clarithromy Myoconda; Myoconda is a formulation of Active Infection Status by indication cin + RHB-104; rifabutin + clarithromycin + ranging from clofazimine RHB104; clofazimine, under development Preclinical to Phase + rifabutin clarithromycin + by RedHill Biopharma for the II clofazimine + treatment of Mycobacterium others avium paratuberculosis (MAP) infection in Crohn’s disease (CD), rheumatoid arthritis (RA) and non-tuberculous mycobacterial infection. claudiximab GC182 iMAb; Claudiximab (iMAB-362) is a Active Cancer, Status by indication GC182, chimaeric Mab targeting gastrointestinal, ranging from Ganymed claudin 18.2 (GC182, a splice pancreatic, Preclinical to Phase variant of claudin 18), under ovarian III development by Astellas cobitolimod DIMS 0150; Cobitolimod (Kappaproct; Active Colitis, ulcerative Phase III Clinical Kappaproct DIMS-0150) is an antisense Inflammatory Trial inhibitor of the p65 protein, a bowel disease, key activator of the NF-kappaB unspecified pathway and toll-like receptor 9 Cancer, brain (TLR9) agonist, under development by InDex Pharmaceuticals for the treatment of ulcerative colitis (UC) codrituzum GC-33; GC33; Codrituzumab (GC-33) is an Active Cancer, liver Phase II Clinical ab RG-7686; anti-glypican 3 mAb, under Trial RG7686; RO development by Chugai 5137382; (Roche) for the treatment of RO5137382; liver cancer. Chugai is also anti-human developing a companion glypican-3 diagnostic for use with GC-33 antibody, once it is launched. A Chugai; companion diagnostic is under codrituzumab development with GC-33 in order to determine the level of glypican-3 expression in hepatocellular carcinoma patients. danoprevir ASC-08; Danoprevir (ITMN-191; RG- Active Infection, Registered ASC08; 7227; RO-5190591) is the lead hepatitis-C virus Ganovo; ITMN in a series of orally available B; small-molecule NS3/4 protease inhibitors.
Page 366 | 477 defactinib PF 04554878; Defactinib is a focal adhesion Active Cancer, Phase II PF 4554878; kinase (FAK) inhibitor, under ovarianCancer, PF-04554878; development by Verastem mesothelioma PF-4554878; Oncology for the treatment of VS 6063; VS- cancer. It is also being 6063; investigated for the treatment of defactinib; mesothelioma cancer defactinib hydrochloride deferasirox Exjade; Exjade Deferasirox (ICL-670; Exjade) Active Haemochromatosi Launched (dispersible is an oral once-daily iron s, secondary Launched tablet); Exjade chelator, developed by Novartis Thalassaemia (film-coated for the treatment of chronic iron tablet); Exjade overload. (granules) dodecafluor NVX-108; NVX-108 is an injectable Active Cancer, brain Phase II Clinical opentane, NVX108; emulsion of Trial NuvOx dodecafluorope dodecafluoropentane, under ntane, NuvOx development by NuvOx Pharma using its dodecafluoropentane (DDFP)-based oxygen therapeutics platform for the treatment of cancer. It makes cancer tumours more susceptible to radiation therapy. dovitinib CHIR-258; Dovitinib lactate (TKI-258; Active Solid and liquid Preclinical lactate formerly CHIR-258) is an tumors of various orally active tyrosine kinase types inhibitor, under development by Oncology Venture for the treatment of breast and liver cancer. duligotuzu MEHD-7945A Duligotuzumab (MEHD- Active Cancer, solid Phase I mab 7945A) is a dual action tumors HER3/EGFR specific phage- derived humanized antibody under development by Genentech (Roche) for the treatment of cancer. emibetuzum LA-480; Emibetuzumab (LY-2875358; Active Cancer; selected Phase II Clinical ab LA480; LY- LA-480) is a humanized IgG4 solid tumors Trial 2875358; Mab that inhibits the HGF- LY2875358; c- dependent and HGF- Met humanized independent c-Met pathway, Mab, Lilly; under development by Eli Lilly cMet Mab, Eli for the treatment of cancer Lilly; cMet Mab, Innovent Biologics; emibetuzumab encorafenib Braftovi; LGX Encorafenib (ONO-7702) is a Active Cancer; solid and RegisteredPhase III 818; LGX-818; B-raf kinase inhibitor, liquid tumors Clinical TrialPhase II LGX818; NVP- developed by Array BioPharma LGX818; ONO for the treatment of cancer. 7702; ONO- 7702; ONO7702; encorafenib enoblituzu MGA-271; Enoblituzumab (MGA-271) is a Active Cancer; solid Phas 1 and Phase 2 mab MGA271; therapeutic humanized Fc- tumors depending on enoblituzumab optimized mAb, under indication development by MacroGenics for the treatment of multiple solid tumours.
Page 367 | 477 ensituximab NEO 101, Ensituximab (NPC-1C) is a Active Cancer, colorectal Phase II Clinical Neogenix; chimaeric Mab, under Cancer, pancreatic Trial NEO-101, development by Precision Phase II Clinical Neogenix; Biologics (formerly Neogenix) Trial NEO-101, targeting specific tumour- Precision; NPC- associated antigens (TAAs), for 1; NPC-1C; the treatment of pancreatic and NPC-2; Neo- colon cancer. The specific 102; target is unknown; however, it ensituximab is believed to be developmentally regulated and not linked to growth factor receptors. entrectinib NMS-E628; Entrectinib (RXDX-101; NMS- Active Cancer, solid, Phase III Clinical NMSE628; RG E628; RG-6268) is an orally unspecified Trial 6268; RG-6268; available small molecule Cancer, lung, non- Phase II Clinical RG6268; inhibitor of ALK, under small cell Trial RXDX-101; development by Nerviano RXDX101; Medical Sciences for the entrectinib treatment of ALK dependent malignancies particularly anaplastic large cell lymphoma and EML4-ALK positive non- small cell lung cancer. enzalutamid ASP-9785; Enzalutamide (MDV-3100) is Active Cancer, prostate Launched e ASP9785; the lead in a series of oral, Cancer, liver Discontinued ENZA; MDV- once-daily, small-molecule Cancer, breast Discontinued 3100; MDV- androgen antagonist 3100 (capsule); compounds (the MDVN 300 MDV-3100 series), developed by (tablet); Medivation (Pfizer) for the MDV3100; treatment of hormone- MDV3100 refractory prostate cancer (capsule); (HRPC). MDV3100 (tablet); erlotinib CP-358774; Erlotinib (Tarceva) is an orally Active Cancer, lung, non- LaunchedLaunchedPr NSC 718781; active epidermal growth factor small cellCancer, e-registrationPhase II OSI-774; R- receptor (EGFR) kinase pancreaticCancer, Clinical TrialPhase II 1415; R1415; inhibitor, developed by OSI brainCancer, RG 1415; RG- Pharmaceuticals as a tumour biliary 1415; RG1415; growth inhibitor. Ro-50-8231; Ro50-8231; Tarceva; erlotinib; erlotinib hydrochloride etrolizumab PRO-145223; Etrolizumab (RG-7413; Active Colitis, ulcerative Phase III Clinical PRO-145223 rhuMAb Beta7) is a humanized Crohn’s disease Trial (IV); PRO- IgG1 anti-ß7 integrin subunit Phase III Clinical 145223 (SC); Mab, under development by Trial PRO145223; Genentech (Roche) for the PRO145223 treatment of ulcerative colitis (IV); (UC). It is also under PRO145223 development for Crohn’s (SC); disease (CD). farletuzuma MORAb-003; Farletuzumab (MORAb-003) is Active Cancer; various Phase I and II b MORAb003; a humanized IgG1 Mab solid tumors depending on farletuzumab targeting folate receptor alpha, indication under development by Morphotek (Eisai) for the treatment of cancer.
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FF-284 CH5-183284; FF-284 (Debio-1347) is an Active Cancer, solid, Phase I Clinical Trial CH5183284; orally available small molecule unspecified Preclinical Debio 1347; fibroblast growth factor Cancer, biliary Debio-1347; receptor (FGFR) 1, 2, 3 FF-284; FF284 inhibitor, under development by Chugai (Hoffmann-La Roche) for the treatment of cancer.
FPA-150 FPA 150; FPA- FPA-150 is a fully human, Active Cancer, solid, Phase I Clinical Trial 150; FPA150; afucosylated monoclonal unspecified anti-B7-H4 antibody targeting B7-H4, antibody, Five under development by Five Prime Prime Therapeutics for the Therapeutics treatment of cancer. FSM-26 FSM-26; FSM-26 is a monoclonal Active Fibrosis, Preclinical FSM26 antibody under development by pulmonary, Preclinical Fibrostatin, targeting a high idiopathic molecular weight (HMW) Diabetes, Goodpasture antigen binding undisclosed Type protein (GPBP) kinase activity for the treatment of idiopathic pulmonary fibrosis (IPF) and diabetes using its proprietary GPBP technology. It also inhibits epithelial-to- mesenchymal transition (EMT). FST-12 FST-12; FST12; FST-12 is under development Active Cancer, lung, non- Preclinical T-12, by Fibrostatin, targeting a high small cell FibroStatin; molecular weight (HMW) T12, FibroStatin Goodpasture antigen binding protein (GPBP) kinase activity which inhibits epithelial-to- mesenchymal transition (EMT) for the treatment of advanced non-small cell lung cancer (NSCLC) using its proprietary GPBP technology. gallium 177-Lu-DOTA- Gallium (68Ga)-edotreotide has Active Diagnosis, cancer Launched (68Ga)- octreotate, been developed by Advanced edotreotide companion Accelerator Applications diagnostic; 177- lutetium- DOTA0-Tyr3- octreotate, companion diagnostic GDC-0084 GDC 0084; GDC-0084 is a small molecule Active Cancer, brain Phase II Clinical GDC-0084; RG- PI3 kinase and mTOR kinase Trial 7666; RG7666 inhibitor as well as an inhibitor of the AKT pathway, under development by Kazia Therapeutics (previously Novogen) for the treatment of cancer.
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GGTI-2418 GGTI-2418; GGTI-2418 is a synthetic Active Cancer, Phase I Clinical Trial GGTI2418; peptidomimetic inhibitor of haematological, Phase I Clinical Trial PTX-100; geranylgeranyltransferase I unspecified Preclinical PTX100 (GGTase I) that appears to Cancer, solid, induce apoptosis by unspecified downregulating many pivotal oncogenic and tumour survival pathways. Under development for the treatment of hematological cancer, myeloma, breast, pancreatic and other cancers using its GGTI technology. ibandronic BM-210955; Ibandronic acid (ibandronate Widely OsteoporosisHype LaunchedLaunchedD acid Bandronat; sodium hydrate) is a 3rd- Launched rcalcaemia of iscontinuedDiscontin Bonat; generation nitrogen-containing malignancyCancer ued Bondenza; bisphosphonate, developed by , myelomaPain, Bondronat; Roche for the treatment of bone cancer Bondronat (IV); disorders such as Bondronat hypercalcaemia of malignancy, (oral); Boniva metastatic bone disease, sodium hydrate; osteolysis, Paget’s disease and ibandronic acid; osteoporosis. ibandronic acid (IV); ibandronic acid (once- monthly); ibandronic acid (oral) ibrutinib CRA 032765; Ibrutinib (PCI-32765) is an Active Cancer, Launched CRA 032765 orally active, small molecule, lymphoma, mantle Launched (capsule); CRA- selective Bruton’s kinase (Btk) cell Launched 032765; CRA- inhibitor, developed by Cancer, Launched 032765 Pharmacyclics for the treatment leukaemia, chronic Registered of B-cell lymphomas (including lymphocytic Phase III Clinical NHL, CLL and Ewing’s Waldenstrom’s Trial sarcoma) hypergammaglobu Phase III Clinical linaemia Trial Graft-versus-host Phase III Clinical disease Trial Phase III Clinical Trial
ID- CMB 305; ID-CMB305 is a cancer Active Cancer, sarcoma, Phase III Clinical CMB305 CMB-305; immunotherapy product synovial Trial CMB305; ID- candidate combining both ID- Cancer, sarcoma, Phase II Clinical CMB305; LV305 and ID-G305 (prime- soft tissue Trial IDCMB305 boost), generated from the Zvex discovery and GLAAS platform. idasanutlin Nutlins; RG- Idasanutlin (RG-7388) is a Active Cancer, Phase III Clinical 738; RG-7388; small molecule that activates leukaemia, acute TrialPhase II Clinical RG738; the p53 pathway by preventing myelogenousCanc TrialPhase II RG7388; RO- the binding between the p53 er, lymphoma, 5503781; and its inhibitor MDM2, for the follicular RO5503781; treatment of cancer
Page 370 | 477
IMAB-027 GT-512; IMAB-027 is a monoclonal Active Cancer, ovarian Phase II Clinical GT512; antibody which selectively Cancer, peritoneal Trial GT512iMAB; binds to the cell surface protein Cancer, fallopian Phase II Clinical IMAB-027; claudin-6 (CLDN6), a protein tube Trial IMAB027; present in a wide range of Cancer, lung, non- Phase II Clinical iMAB-512; cancers, including testicular, small cell Trial iMAB512 ovarian, uterine, and lung cancers, but absent in healthy tissue. IMO-8400 IMO-8400; IMO-8400 is an oligonucleotide Active Dermatomyositis Phase II Clinical IMO8400 antagonist of endosomal toll- Autoimmune Trial like receptor (TLR) 7, 8 and 9, disease, Preclinical under development by Idera unspecified Pharmaceuticals for the Waldenstrom’s treatment of dermamyositis and hypergammaglobu autoimmune diseases including linaemia plaque psoriasis. ipatasertib GDC-0068; Ipatasertib (RG-7440; GDC- Active Cancer, breast Phase III Clinical GDC0068; RG- 0068) is an orally active Akt Cancer, prostate Trial 7440; RG7440; inhibitor, under development by Cancer, Phase III Clinical ipatasertib Genentech (Hoffmann-La gastrointestinal, Trial Roche) for the treatment of stomach Phase II Clinical cancer. Cancer, gastro- Trial oesophageal Phase II junction irinotecan, BAX 2398; PEP-02 (SHP-673) is a Active Cancer, LaunchedPhase III PharmaEngi BAX-2398; nanoliposomal formulation of pancreaticCancer, Clinical TrialPhase II ne BAX-2399; irinotecan, developed by lung, small Clinical TrialPhase II BAX2398; Merrimack (Hermes cellCancer, Clinical TrialPhase I BAX2399; Biosciences before the gastrointestinal, Clinical Trial CPT-11, acquisition) for the treatment of stomachCancer, nanoliposomal; cancer. gastro- I oesophageal junction
IT-139 IT-139; KP IT-139 (NKP-1339) is a first- Active Cancer, lung, non- Phase I Clinical Trial 1339; KP-1339; in-class small molecule GRP78 small cell Phase I Clinical Trial KP1339; NKP- inhibitor, under development by Cancer, 1339; NKP-14; Intezyne Technologies (Niiki neuroendocrine NKP1339; Pharma before the acquisition) NKP14 for the iv treatment of cancer. ivosidenib AG 120; AG- Ivosidenib is an orally available Active Cancer, Launched 120; AG120; therapy targeting the mutated leukaemia, acute Phase III Clinical CS 3010; CS- form of isocitrate myelogenous Trial 3010; CS3010; dehydrogenase 1 (IDH1), IDH1 inhibitor, developed by Agios Agios; Tibsovo; Pharmaceuticals for the brain cancer treatment of brain cancer, solid therapy, Agios tumours and haematological Pharmaceuticals malignancies. ; brain cancer therapy, Celgene; ivosidenib JPH-203 JPH-203; JPH-203 is under development Active Cancer, solid, Phase I Clinical Trial JPH203 by J-Pharma for the treatment unspecified Preclinical of cancer. It targets L-type Cancer, biliary amino acid transporter 1 inhibitor (LAT-1) (Company pipeline, J-Pharma, 19 Apr 2013, http://www.j- pharma.com/index_e.html).
Page 371 | 477 lapatinib GW-2016; GW- Lapatinib ditosylate (GW- Active Cancer, LaunchedPhase III ditosylate 572016; GW- 572016) is an oral, once-daily breastCancer, Clinical TrialPhase 572016F; ErbB-2 and EGFR dual kinase oesophagealCance III Clinical GW572016; inhibitor, developed by r, gastro- TrialPhase II Clinical NSC 727989; GlaxoSmithKline (GSK) for the oesophageal Trial NSC-727989; treatment of solid tumours in junctionCancer, Tycerb; Tykerb; which these receptors are pancreaticCancer, Tyverb; overexpressed, including breast, renalCancer, lapatinib; nsclc and gastric cancers. bladderCancer, lapatinib colorectal ditosylate larotrectinib LOXO-101; Larotrectinib is a Trk kinase Active Cancer, solid, Pre-registration LOXO-101 inhibitor, under development by unspecified Phase II Clinical (capsule); Array BioPharma and Loxo Cancer, lung, non- Trial LOXO-101 Oncology for the treatment of small cell Phase II Clinical (oral liquid); cancer. The programme targets Cancer, sarcoma, Trial LOXO101; a specified novel oncogenic soft tissue Phase II LOXO101 activating mutation. Its lead Cancer, thyroid (capsule); clinical programme is a potent LOXO101 (oral and selective Trk kinase liquid); inhibitor anticancers, Array-5; anticancers, Loxo; larotrectinib; larotrectinib (capsule); larotrectinib (oral liquid) lebrikizuma Anti-IL13, Lebrikizumab (MILR-1444A) Active Eczema, atopic Phase II Clinical b Genentech; is a humanized Mab against IL- Cancer, Trial MILR-1444A; 13, under development by lymphoma, No Development MILR1444A; Dermira for the prevention of Hodgkin’s Reported PRO-301444; atopic dermatitis. It was also Fibrosis, PRO301444; under development for the pulmonary RG-3637; treatment of cancer RG3637; RO- 5490255; RO5490255; TNX-650; TNX650; anti- IL13 mAb, Genentech; lebrikizumab lenalidomid CC 5013; CC Lenalidomide (Revlimid; Active Cancer, LaunchedLaunchedL e 5053; CC-5013; formerly Revimid) is a class I myelomaMyelody aunchedLaunchedLa CC-5053; CDC thalidomide analogue (ImiD), splastic unchedPhase III 501; CDC 5013; developed by Celgene for the syndromeAnemia, Clinical TrialPhase CDC-501; treatment of cancer. It was also unspecifiedCancer III Clinical CDC-5013; under development for , lymphoma, TrialPhase III ImiDs, class I, rheumatoid arthritis, mantle cellCancer, Celgene; lymphoma, T-cell Revlimid; lenalidomide
Page 372 | 477 leucine + NS-0200; PDE5 NS-0200 is a fixed-dose Active Non-alcoholic Phase II Clinical metformin inhibitor + combination of leucine + steatohepatitis Trial + PDE5 leucine + metformin + sildenafil, under Obesity Phase II Clinical inhibitor, metformin, development by NuSirt Trial NuSirt NuSirt Biopharma for the treatment of Biopharma Biopharma; non-alcoholic fatty liver disease leucine + (NAFLD) and non-alcoholic metformin + steatohepatitis (NASH). The PDE5 inhibitor, combination activates the NuSirt sirtuin pathway. Biopharma; leucine + metformin + sildenafil; leucine/metform in/sildenafil; LOR-253 APTO 253; APTO-253 (formerly LT-253, Active Cancer, colorectal Phase I Clinical Trial APTO-253; LOR-253) is a small molecule Cancer, lung, non- Phase I Clinical Trial APTO-253 HCl; Kruppel-like factor 4 (KLF4) small cell APTO253; inducer, under development by Cancer, LOR-253; LOR- Lorus Therapeutics for the leukaemia, acute 253 HCl; treatment of solid tumours myelogenous LOR253; LT- Cancer, 253; LT253; lymphoma, ML series, Hodgkin’s Lorus; ML-133; ML-225; ML133; ML225
LOXO-292 LOXO 292; LOXO-292 is a RET Active Cancer, solid, Phase I Clinical LOXO-292; (rearranged during transfection) unspecifiedCancer TrialPhase I Clinical LOXO292; RET kinase inhibitor, under , lung, non-small TrialPhase I Clinical inhibitors, Array development by Array cellCancer, TrialPhase I Clinical BioPharma; BioPharma and Loxo Oncology thyroidCancer, Trial RET inhibitors, for the treatment of non-small colorectal Loxo Oncology cell lung cancer and cancers of thyroid and colon. lumretuzum RG-7116; Lumretuzumab (RG-7116) is a Active Cancer, lung, non- Phase I Clinical Trial ab RG7116; RO- glyco-engineered humanized small cell Phase I Clinical Trial 5479599; Mab developed to inhibit the Cancer, solid, Phase I Clinical Trial RO5479599; activation and signaling of unspecified Phase I Clinical Trial lumretuzumab HER3, under development by Cancer, colorectal Phase I Clinical Trial Hoffmann-La Roche for the Cancer, head, and Discontinued treatment of cancer. It is neck designed to engage the immune Cancer, ovarian system when bound to tumour Cancer, breast cells and elicit enhanced antibody-dependent cellular cytotoxicity (ADCC) MAN-01 MAN-01; MAN-01 is under development Active Glaucoma Preclinical MAN-01, Q by Mannin Research, for the Pain, cancer Preclinical BioMed; treatment of primary open angle MAN01 glaucoma. MEDI-3902 MEDI-3902; MEDI-3902 is a bispecific anti- Active Infection, Phase II Clinical MEDI3902; Psl/PcrV Mab engineered to pseudomonal Trial PcrV antibody, combine 3 distinct mechanisms prophylaxis AstraZeneca of action, under development by MedImmune (AstraZeneca) for the prevention of nosocomial pneumonia caused by Pseudomonas aeruginosa.
Page 373 | 477 midostaurin CGP 41251; Midostaurin (PKC-412) is an Active Cancer, LaunchedLaunchedP CGP 41251 oral staurosporin derivative that leukaemia, acute hase II Clinical (capsule); CGP acts as a protein kinase C myelogenousMast TrialPhase I Clinical 41251 inhibitor, developed by ocytosisCancer, TrialPhase I Clinical (solution); CGP- Novartis for the treatment of leukaemia, acute Trial 41251; cancer. It targets c-kit kinase in lymphocyticCance aggressive systemic r, mastocytosis (ASM). colorectalMyelody splastic syndrome MM-151 MM 151; MM- MM-151 is an oligoclonal Active Cancer, solid, Phase I Clinical Trial 151; MM151 therapeutic consisting of a unspecified Phase I Clinical Trial mixture of 3 human antibody Cancer, colorectal Phase I Clinical Trial antagonists targeting the ErbB1 Cancer, lung, non- Phase I Clinical Trial pathway, under development by small cell Phase I Clinical Trial Merrimack for the treatment of Cancer, breast Phase I Clinical Trial solid tumour cancer Cancer, pancreatic Cancer, head, and neck navitoclax A-855071.0; A- Navitoclax is an orally Active Cancer, Phase II Clinical 855071.0 bioavailable Bcl-2 family lymphoma, mantle TrialPhase II Clinical (capsule); A- kinase inhibitor, under cellCancer, TrialPhase II Clinical 855071.0 (oral development by AbbVie lymphoma, T-cell, TrialPhase II Clinical solution); A- (formerly Abbott) as a cutaneousCancer, TrialPhase II Clinical 855071.0 proapoptotic anticancer. It is a lymphoma, T-cell, TrialPhase I Clinical (tablet); A- 2nd-generation molecule to peripheralCancer, TrialPhase I Clinical 855071.3; ABT-737 (qv), which was lymphoma, TrialPhase I Clinical orally non-bioavailable. It follicularMyelofib Trial mimics BAD and acts on rosisCancer, preprimed apoptotic cells by lymphoma, non- removing survival signaling. It Hodgkin’s has demonstrated efficacy as a monotherapy and in combination with chemotherapy. Nexvax 2 Nexvax 2; Nexvax 2 is a non-dietary Active Coeliac disease Phase II Clinical Nexvax2; therapeutic vaccine under Trial Nexvax2 development by ImmusanT (intradermal); (formerly Nexpep) for the Nexvax2 (sc); treatment of coeliac disease. coeliac disease therapy, BTG; coeliac disease therapy, Nexpep nilotinib AMN-107; Nilotinib (AMN-107) is a Active Cancer, Launched AMN107; signal transduction inhibitor, leukaemia, chronic Phase II Clinical Tasigna; developed by Novartis as an myelogenous Trial nilotinib oral capsule for the treatment of Cancer, Phase II Clinical cancer and pulmonary arterial leukaemia, acute Trial hypertension (PAH) ( lymphocytic Phase II Clinical Cancer, Trial leukaemia, Phase II Clinical Trial NMI-350 NMI-300; NMI- NMI-300 is a folate receptor Active Cancer, ovarian Phase I Clinical Trial 350; NMI-351; alpha antagonist, under Cancer, solid, Phase I Clinical Trial NMI-352; development by Nemucore unspecified NMI300; Medical Innovations for the NMI350; treatment of ovarian cancer and NMI351; other solid tumors. NMI352
Page 374 | 477 onapristone Apristor; Onapristone (IVV-1001) is an Active Cancer, Phase II Clinical Apristor oral anti-progestin hormone breastCancer, TrialPhase II Clinical (immediate blocker, under development by endometrialCancer TrialPhase II Clinical release); Context Therapeutics for the , ovarianCancer, TrialPhase II Clinical Apristor treatment of cancer. It had prostateCancer, TrialPhase II Clinical (sustained potential for the treatment of sarcoma, TrialPhase II Clinical release); IVV endometrial and other cancers. unspecifiedMenstr Trial 1001; IVV 1001 ual disorder, (immediate unspecified release); IVV 1001 osimertinib AZD-9291; Osimertinib (AZD-9291) is a Active Cancer, lung, non- Launched AZD-9291 (IV); 3rd generation tyrosine kinase small cell Phase I Clinical Trial AZD-9291 inhibitor (TKI) targeting EGFR Cancer, liver Phase I Clinical Trial (capsule); AZD- activating (EGFRm+) and Cancer, solid, 9291 (solution); resistance (T790M) mutations, unspecified AZD-9291 developed by AstraZeneca for (tablet); the treatment of nsclc. AZD9291 peginterfero Exxura; Exxura Peginterferon alfa-2a (Pegasys) Active Infection, Launched n alfa-2a (IV); Exxura is a PEG-modified recombinant hepatitis-C virus Launched (SC); PEG IFN interferon alpha-2a (PEG- Infection, Phase III Clinical alpha-2a; PEG IFNalpha-2a), developed by hepatitis-B virus Trial IFN alpha-2a Roche as an antiviral agent Infection, No Development (IV); PEG IFN (Ann Rep, 1993; Scrip, 1998, hepatitis-D virus Reported alpha-2a (SC); 2349, 22). Infection, No Development PEG-IFN alfa- HIV/AIDS Reported 2a BA-free Cancer, melanoma No Development formulation Cancer, Reported (sc); PEG- leukaemia, chronic No Development IFNalpha-2a, myelogenous Reported Roche; PEG- Cancer, renal IFNalpha-2a,
PEGPH20, PEG-PEM; PEGPH20 (PEG-rHuPH20) is a Active Cancer, Phase III Clinical Halozyme PEG-rHuPH20; pegylated recombinant human pancreaticCancer, TrialPhase II Clinical PEGPH-20; hyaluronidase, under lung, non-small TrialPhase II Clinical PEGPH20; development by Halozyme for cellCancer, TrialPhase II Clinical PEGPH20, use in combination with breastCancer, TrialPhase II Clinical Halozyme; chemotherapeutics as an bladderCancer, TrialPhase II Clinical PEGylated anticancer agent. biliaryCancer, TrialPhase I Clinical recombinant gastrointestinal, TrialPhase I Clinical human stomachCancer, TrialPreclinical hyaluronidase, solid, Halozyme; unspecifiedCancer anticancer , prostateCancer, therapy , liver Halozyme; pegylated- rHuPH20
Page 375 | 477 pembrolizu 89Zr Pembrolizumab is a humanized, Active Cancer, melanoma Launched mab pembrolizumab; anti-programmed cell death 1 Cancer, lung, non- Launched 89Zr- (PD-1) monoclonal IgG4 small cell Launched pembrolizumab; antibody, developed by Merck Cancer, head, and Launched Keytruda; MK & Co (Schering-Plough before neck Launched 3475; MK- the merger) for the treatment of Cancer, Launched 3475; MK3475; cancer. lymphoma, Launched SCH 900475; Hodgkin’s Launched SCH-900475; Cancer, bladder Launched SCH900475; Cancer, Launched lambrolizumab; gastrointestinal, Launched pembrolizumab stomach pemigatinib INCB-054828; Pemigatinib (INCB-54828) is a Active Cancer, solid, Phase II Clinical INCB-54828; FGFR kinase inhibitor, under unspecifiedCancer TrialPhase II Clinical INCB054828; development by Incyte , lung, non-small TrialPhase II Clinical INCB54828; Corporation for the treatment of cellCancer, TrialPhase II Clinical pemigatinib solid cancer. gastrointestinal, Trial stomachCancer, endometrial pertuzumab 2C4 antibody, Pertuzumab (2C4 antibody; Active Cancer, breast Launched Genentech; RG-1273; Omnitarg) is a Cancer, solid, Phase III Clinical Omnitarg; humanized Mab targeting the unspecified Trial Perjeta; R-1273; HER2-based signaling pathway, Cancer, ovarian Phase III Clinical R1273; RG- developed by Genentech Cancer, lung, non- Trial 1273; RG1273; (Roche) for use as a small cell Phase II Clinical RO-4368451; combination agent for breast Cancer, peritoneal Trial RO4368451; and ovarian cancer and as a Cancer, prostate No Development pertuzumab; single agent in other cancers. Reported rhuMAb 2C4 pinometosta DOT1L HMT Pinometostat (EPZ-01; EPZ- Active Cancer, Phase I Clinical Trial t inhibitor, 004777) is a small molecule leukaemia, acute Phase I Clinical Trial Epizyme; DOT1L histone myelogenous Phase I Clinical Trial DOT1L methyltransferase (HMT) Cancer, inhibitor, inhibitor, under development by leukaemia, acute Epizyme; EPZ Epizyme in partnership with lymphocytic 5676; EPZ- Celgene for the treatment of 004777; EPZ- mixed lineage leukaemia 01; EPZ-5676; (MLL), acute myeloid leukemia EPZ004777; (AML) and acute lymphoblastic EPZ01; leukemia (ALL). It selectively EPZ5676; kills the MLL cells with pinometostat chromosomal alteration. QBECO QBECO; QBECO is a site-specific Active Crohn’s Phase II Clinical QBECO SSI; immunotherapy (SSI), under diseaseColitis, TrialPhase II Clinical SSI QBECO; development by Qu Biologics ulcerativeCancer, Trial colon SSI for the treatment of Crohn’s colorectalCancer, disease (CD) and ulcerative pancreaticCancer, colitis (UC). It contains killed lung, unspecified bacterial components from a single bacterial species known to be a common cause of infection in an organ or tissue.
Page 376 | 477 quizartinib AC-220; AC- Quizartinib dihydrochloride Active Cancer, Phase III Clinical dihydrochlo 220 (solution); (AC-220) is a small molecule leukaemia, acute Trial ride AC-220 (tablet); FLT3 kinase inhibitor, under myelogenous Phase I Clinical Trial AC010220; development by Ambit Cancer, AC010220 Biosciences for the treatment of leukaemia, acute (solution); cancer including acute myeloid lymphocytic AC010220 leukaemia (AML) patients with Cancer, solid, (tablet); AC220; an FLT3 mutation resulting in unspecified AC220 overexpression Myelodysplastic (solution) syndrome
Re-188 BAY86-5284; Re-188 P2045 was a Active Cancer, lung, non- Phase I Clinical Trial P2045 P-2045, Re-188; somatostatin 2 receptor agonist, small cell Phase I Clinical Trial P2045, Re-188; which was under development Cancer, lung, Re-188 P2045; by Diatide (Bayer (formerly small cell Rhenium Re Bayer Schering Pharma)) as an Cancer, pancreatic 188 P2045; anticancer. It consists of a Cancer, renal Tozaride; synthetic peptide analogue of rhenium-188 somatostatin which targets P2045 somatostatin receptors that are overexpressed by several types of cancer, combined with rhenium-188 which emits ß radiation to destroy tumour cells
RO- CH 5126766; RO-5126766 (RG-7304) is a Active Cancer, Phase I Clinical 5126766 CH-5126766; dual Raf and MEK inhibitor, melanomaCancer, TrialPhase I Clinical CH5126766; under development by Chugai lung, non-small TrialPhase I Clinical CK-I27; CKI- (Roche) for the treatment of cellCancer, TrialPhase I Clinical 27; CKI27; R- solid tumours. pancreaticCancer, Trial 7304; R7304; solid, unspecified RG-7304; RG7304; RO- 5126766; RO5126766 rucaparib AG-014699; Rucaparib is a small molecule Active Cancer, ovarian Launched AG-014699 inhibitor of PARP 1, 2 and 3, Cancer, fallopian Registered (IV); AG- developed by Clovis Oncology tube Registered 014699 (oral); for the treatment of cancer Cancer, peritoneal Phase III Clinical AG-140699; Cancer, prostate Trial AG-140699 Cancer, bladder Phase II Clinical (IV); AG- Cancer, breast Trial 140699 (oral); Phase II AG-14699; AG- 14699 (IV); seribantuma MM 121; MM- Seribantumab (MM-121; SAR- Active Cancer, breast Phase II Clinical b 121; MM121; 256212) is a fully human Cancer, lung, non- Trial SAR 256212; monoclonal antibody, under small cell Phase II Clinical SAR-256212; development by Sanofi under Cancer, ovarian Trial seribantumab license from Merrimack for the treatment of breast cancer and non-small cell lung cancer sonidegib LDE-225; LDE- Sonidegib (LDE-225; NVP- Active Cancer, basal cell Launched 225 (oral); LDE225) is an orally active and brain, sarcoma, Phase II Clinical LDE-225 topical SMO (smoothened) rhabdomyo, liver Trial (topical); LDE- inhibitor, developed by osteo Phase II Clinical 225B; LDE225; Novartis for the treatment of Cancer, Trial LDE225 (oral); cancer. Development of a neuroblastoma Phase II LDE225 topical cream formulation for Cancer, solid, (topical); the treatment of Gorlin unspecified LDE225B; syndrome was terminated due to lack of tumour clearance
Page 377 | 477 susatoxuma MEDI-4893; Susatoxumab (MEDI-4893) is Active Infection, Phase II Clinical b MEDI4893; an extended half-life human staphylococcalInfe TrialPhase II Clinical susatoxumab; IgG1 Mab targeting ction, pneumonia, TrialPhase I Clinical suvratoxumab Staphylococcus aureus alpha- hospital- TrialPhase II Clinical toxin, under development by acquiredInfection, Trial AstraZeneca for the treatment MRSAInfection, of S aureus infections, staphylococcal including MRSA and ventilator prophylaxis associated pneumonia (VAP) tamoxifen Ceadan; ICI- Tamoxifen is an antiestrogen, Widely Cancer, breast Launched 46474; Istubal; developed by AstraZeneca for Launched Kessar; Nolgen; the palliative treatment of Nolvadex; breast cancer and the treatment Novaldex; of anovulatory infertility. Tafoxen; A companion diagnostic has Tamofen; been developed to identify Tamoplex; breast cancer patients whose Tamoxasta; tumours show ER/PgR Tamoxen; expression. Tomaxen; Valodex; tamoxifen; tamoxifen citrate tavokinogen DNA IL-12, Tavokinogene telsaplasmid is a Active Cancer, Merkel Phase II Clinical e OncoSec DNA plasmid construct coding cell carcinoma Trial telsaplasmi Medical; IL-12, for interleukin-12 (IL-12) as an Cancer, melanoma Phase II Clinical d OncoSec immunotherapeutic agent Cancer, head, and Trial Medical; IT- delivered using OMS delivery neck Phase II Clinical pIL12-EP; system, under development by Cancer, breast Trial immunopulse OncoSec Medical for the Cancer, solid, Phase I Clinical Trial program, treatment of melanoma, Merkel unspecified Preclinical OncoSec cell carcinoma and cutaneous Cancer, No Development Medical; pIL- T-cell lymphoma. lymphoma, T-cell, Reported 12; plasmid cutaneous DNA encoding human interleukin-12, OncoSec Medical; plasmid interleukin-12, OncoSec Medical; tavo; tavo-EP; tavokinogene telsaplasmid tazemetosta E-7438; E-7438 Tazemetostat (E-7438 (EPZ- Active Cancer, Phase II Clinical t (oral 5687)) is an orally available, lymphoma, non- TrialPhase II Clinical suspension); E- small-molecule histone Hodgkin’sCancer, TrialPhase II Clinical 7438 (oral methyltransferase (HMT) lymphoma, Trial tablet); E7438; inhibitors targeting EZH2, follicularCancer, E7438 (oral under development by Epizyme solid, suspension); for the treatment of non- unspecifiedCancer E7438 (oral Hodgkin’s lymphoma, breast , sarcoma, tablet); EPZ- cancer and synovial sarcoma. synovial 005687; EZH2 targets the catalytic center of a multiprotein complex, polycomb repressive complex 2
Page 378 | 477 tralokinuma CAT-354; CAT- Tralokinumab (CAT-354) is a Active Eczema, atopic Phase III Clinical b 354 (IV); CAT- fully human recombinant Mab Asthma Trial 354 (SC); against interleukin-13 (IL-13) Fibrosis, Discontinued CAT354; under development by Leo pulmonary, Discontinued CAT354 (IV); Pharma for the treatment of idiopathic Discontinued atopic dermatitis. It was Colitis, ulcerative Discontinued previously under development Chronic by Cambridge Antibody obstructive Technology (CAT) pulmonary disease (AstraZeneca) for the treatment of asthma but was discontinued due to failed Phase III trials. Development for ulcerative colitis (UC) and idiopathic pulmonary fibrosis (IPF) was discontinued due to safety and efficacy reasons.
TRC-694 JNJ 6420694; TRC-694 (formerly JNJ- Active Cancer, myeloma Preclinical JNJ-0694; JNJ- 64290694) is a novel, orally Cancer, Preclinical 6420694; JNJ- bioavailable inhibitor of NF-kB haematological, 64290694; inducing kinase (NIK), under unspecified JNJ0694; development by Johnson & JNJ64290694; Johnson (Janssen) for the TRC-694; treatment of hematologic TRC694 malignancies, including myeloma. Janssen has granted Tracon the rights to develop TRC-694 VAL-201 VAL 201; VAL-201 is a 10-amino-acid Active Cancer, Phase II Clinical VAL-201; peptide, under development by prostateCancer, TrialPhase II Clinical VAL201; Cancer Research Technology solid, TrialPreclinicalPrecli VALi-201; (CRT) for the treatment of unspecifiedCancer nicalPreclinical VALi201 hormone-resistant prostate , breastCancer, cancer and other hormone- ovarianEndometri induced growth abnormalities osis including breast and ovarian cancer and endometriosis. It specifically inhibits androgen, estrogen, and EGF-dependent DNA synthesis valganciclo R-127 (syrup); Valganciclovir (RG-127; RG- Widely Infection, Launched vir R-127 (tablet); 1227) is a prodrug derivative of Launched cytomegalovirus No Development R127 (syrup); ganciclovir with improved oral Colitis, ulcerative Reported R127 (tablet); bioavailability, developed by RG-1227; RG- Roche for the treatment of 1227 (solution); CMV disease. It was previously RG-127; RG- also under development for 127 (solution); ulcerative colitis. venetoclax ABT 199; ABT- Venetoclax (RG-7601) is a Active Cancer, Launched 199; ABT199; selective Bcl-2 inhibitor, leukaemia, chronic Pre-registration GDC 0199; developed by AbbVie (formerly lymphocytic Phase III Clinical GDC 199; Abbott) and Genentech Cancer, Trial GDC-0199; (Hoffman-La Roche) for the leukaemia, acute Phase II Clinical GDC-199; treatment of cancer and lupus. myelogenous Trial GDC0199; GDC199; RG 7601; RG-7601; RG7601; Venclexta; Venclyxto; venetoclax Source: Original compilation by author from US-FDA, accessed October 2019 website and Citeline/PharmaProjects, 2019
Page 379 | 477
APPENDIX E INTERVIEW GUIDE (MASTER)
Non-confidential information sought from interviewees at Alpha, Beta and Gamma included the following items that were woven into unstructured conversations:
1. Please describe the general arrangement of physician relationship to the health
system, i.e., employees? Contracted group services?
2. How is patient care integrated across services?
3. Please describe the major historical junctures in the formation of your precision
medicine program.
4. What was the impetus to begin a PM program?
5. Were there key individuals or prime movers in the process? Describe them.
6. When did the institution begin electronic medical records?
7. At what point was data captured for precision medicine?
8. Please describe the bio-banking program.
9. When were EMR and Biobanks linked?
10. Does [Alpha/Beta/Gamma] have any advantages for PM vis-à-
vis the patient population served?
11. To what degree is PM currently integrated into clinical practice? For oncology? Page 380 | 477
For other clinical services?
What are the targets as a percentage of care services for each?
12. What is the degree of physician buy-in according to specialty?
13. What are the key organizational characteristics that enable precision medicine?
14. What are the relevant clinical dynamics for precision medicine to be incorporated
into patient care?
15. Are clinical protocols in place widely or for limited clinical services?
16. How are clinical protocols developed and maintained?
17. What human and financial resources are required?
18. What are the clinical infrastructure requirements?
19. Do cost among different protocols vary widely?
20. Do the overall costs of administering/providing precision medicine vary widely
from traditional care services?
21. Have there been issues with payers for reimbursement?
22. How is the payer relationship managed?
23. Have there been relationship or supply-chain issues with producers?
24. Has your PM program in any way altered your business/revenue model? Page 381 | 477
25. Has your PM program required modification of producers’ business/revenue
model as it relates to your institution? In what way?
26. Does your institution integrate PM research with patient care? If so, how is that
managed financially?
27. How are outcomes monitored and measured? What is the review process? By
whom?
28. Has PM arrived at being the standard of practice for any of the clinical services?
29. If so, how did that evolve?
30. Were there points of resistance along the way in the implementation of PM?
31. Are there any continuing areas of resistance? How are these managed?
32. Are there other issues that you would like to discuss regarding PM at this
institution?
33. Have I missed any significant matters in this interview?
Added after interviews had begun:
34. What are the historical and current ethical issues?
35. What is the evolution of issues surrounding process flow?
Page 382 | 477
APPENDIX F SUMMARY OF INTERVIEWS BY CODING CATEGORY, NODES AND THEMES
Appendix F: Summary of Interviews by Coding Category, Nodes and Themes Note: As a condition of interviewing, direct attribution in any manuscript or publication was not permitted by each of the institutions. The author has coded the interviewees/contributors to the Interview Observations below. The codes will be provided on written request but not for publication or attribution. Coding category Theme/ Theme explored Interview Observations Int. Node # code 1 - the leadership -Unique circumstances of an engaged and powerful CEO’s commitment to I-2 history of precision medicine; precision -Physicians are employees without tenure or a guaranteed contract; medicine at the -Standards of practice driven diabetes care improved outcomes substantially; institution -Sought to answer the question, “How can we hard-wire the evidence-based protocols into the HER and into the clinical workflow in a way that physicians are forced to make the optimal choice; -Confidence to make the rules, design the clinical experiment, and then assess the impact; -Institution serves as the leader’s laboratory; C-1) What are -Goal to be the first institution to sequence every patient; the conditions or -Convince payers that precision medicine saves money in the long run; antecedents? -Research imperative is to help patients now, not with the Nobel Prize in the future.
-Program is a combination of leadership and communal participation. I-5
-Desire is to offer patients something revolutionary. I-1
I-7
Page 383 | 477
-Had allies but never got over the hump of saying, “This is going to be a programmatic strategy for us. Genomics is part of our system strategy. It was written in the system’s strategic plan:” -Our patient population is substantially different, and our care delivery has to adapt to that.” I-12
-Innovative administrators supported experimentation in care. I-14
-Local community of physicians is supportive of the strong culture of I-15, 16 leadership.
-Had support and freedom in a [remote] location that would have not occurred at headquarters; -Tendency at headquarters would have been too much oversight and control with the possibility of power plays; -Individuals in authority cannot be afraid of disruptive innovation which requires you to challenge your own biases; -If you are willing to be innovative you have to be willing to be misunderstood for a long time. -The CEO’s vision is to align [all facilities] into one large federation – there were many reasons to make the change, but precision medicine was not only one of them but was a driver as well; -This vision prioritized the role of the precision medicine program leadership; -Direct reporting and immediate access to the CEO and CMO was a key component of precision medicine adoption; -Top level support became highly visible in 2016 [after the groundwork was laid]; -Physician championship [at the service levels] is the key and occurs when the I-44 specialty leaders have a good experience that leads to shared vision and implementation; -There are no predictable or continuous characteristics of physician champions. Page 384 | 477
-It is all value driven and reflects the mission: respect, integrity, compassion, healing, teamwork, innovation, excellence, and stewardship; -Precision medicine is a Board appointed initiative but is accountable for progress and patient care value month-to-month; -In terms of collegiality there are times when there is healthy debate and everyone’s good intentions are on the table; -First director of precision medicine was appointed in 2008 with successor starting in 2011; -The initiative was top down from the Board level; -Institutional style of management takes all directions into account: managing downward is relational, transparent, fair, and direct; when there are ambiguous issues groups talk through the circumstances on an inclusive basis. When managing laterally there is reliance on communication with peer programs and work style across groups is based on discovery, translation, and application. Initiatives are managed translationally with discovery in the hands of research colleagues. Validation is tested through economic and value study. When managing upwards the approach is to demonstrate the interconnectivity of initiatives across services or departments; precision medicine is overall a strategic hybrid priority and the C-suite understands that. -Planning is long range but expectations are set yearly for the four-precision medicine strategic areas: what does this look like in a year? -Emphasis on avoiding silos; -Shared vision of the evolving role of other omics; -Emphasis on moving beyond oncology over the next two years; -Culture of accountability but not all projects are expected to be successful; -Clarity of definition: “We aspire to be the world’s leaders in clinical implementation of precision medicine. We do not aspire to be research leaders [in basic science of genomics]. -Highlight translational efforts to application more so than the discovery to become the trusted provider; Page 385 | 477
-Major challenge is integrating and providing continuity of genomic data captured now for future use [for individual patients]; I-43 -Addressing at leadership level the questions of what the microbiome and exposome do for health and how to measure that over time.
-Strategic platform is Genomics in Action premised on the theory that genomics will be ubiquitous which demands simplicity, ease of use, affordability and accessibility by patients and providers, and understandable and actionable by physicians on a national basis; -Mission is to meet these goals [here] first; -HER tools for simplicity must occur through collaboration with system vendor; -Genome must be in the HER, interpretable and have exportable clinical decision support functionality; -Task is to make the precision medicine program per se unnecessary, i.e., for the principles to be absorbed int standards of practice across medical services; -Have reached that milestone in oncology where precision medicine has I-24 become the standard of practice; -Rare diseases moving rapidly in that direction; -Other services are still in progress towards standards of practice.
-In order to live up to the reputation, what then must we do? -Comprehensively, it was regenerative medicine, personalized medicine, and the science of health care delivery; -The science of delivery is most relevant because the value of precision medicine must be demonstrated scientifically; -Integration of a hospital system is the foundation of success in meeting patient care objectives; -The role of bioethics was not present at the birth of the program but became part of the support structure;
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-Institution had to play a role in defining the nature and role of precision medicine in the national perspective; it had to go beyond being a diagnostic tool and rallying cry; -Precision medicine had to have relevance and value for medical practice, and this was the basis of translational programs at first then the infrastructural programs that included the microbiome, bioethics, and education; -Building the biobank infrastructure played to success; -The evolution of the oncology program towards standards of practice initially required precision medicine to share risks with oncologists: -we will provide the evidence; -we will provide the way forward; -we will make it easy to order the test; -we will help interpret it -we will create the tumor boards. -Having fulfilled the vision, having oncology as a formal part of precision medicine detracts from its success. -The graduation process began two years ago when it became clear that it was time to push the principles to the rank and file beginning with oncology, pathology, and medical genetics; -5000 people going through the Diagnostic Odyssey program [improving patient care by turning genomic research into real-world personalized medicine applications] this year; -Next frontier—letting-go and refocusing; how much gene therapy should be in precision medicine? -How much multi-omics should now be owned vs. pushed into core services? -How do we define maximum benefit to the patient? How is that defined in the US vs. the rest of the world? -The clinical standard now is do not push things forward unless value for the patient can be demonstrated – we are past the experimental phase, a shift that has not happened at most institutions. -Precision medicine will have to be grassroots going forward. Page 387 | 477
-Beyond thinking that it is the answer to everything precision medicine is arriving at a more realistic plateau. -Those application of precision medicine that have not yet impacted health care will have to be dissected by the next generation of physicians. -Given the complexity [and start-up costs] of precision medicine, it is likely that the haves will have more and the have-nots less. -The transition to precision medicine is happening slowly and not currently in a scalable way, but in five years the pace will change. Fundamentally health care providers always struggle to give answers and are unhappy when they cannot. When a tool is available that gives a better answer, physicians will grab it provided that it does not make them look stupid. If it can be encapsulated, there is an action plan and it does not require too much deviation from daily activity, it will be adopted if not immediately then over time. I-23 -The task is to create pathways that integrate with daily activities, rather than diverge. -Patient expectations have become more forceful; future waves will have more value than in the past.
-There were two shifts on our program towards medicines and pharmacogenomics. -These heightened the necessity for structured education. 9 -human and -The precision medicine program is internally funded at $15 to $20 million per I-2 financial year with an additional $15 to $20 million in external grants and contracts; resources required -Biggest growth is from the NIH -30 to 40 dedicated precision medicine research faculty -Most clinicians are connected to a researcher.
-For efficiency added a shared services group currently with 45 people; I-14 -Overall staffing in precision genomics is 175 to 200; -Ironically growing too fast but still in a start-up mode; -Still need to recruit, hire and retain subject matter experts; Page 388 | 477
-Necessary to transform the medical informaticists to bio-informaticists and develop a new job category with description -Every new job required a position description from scratch; -Formally have a hierarchy structure but operate horizontally in practice.
-There was enough internal support to get up and running but made an initial I-15, 16 decision to focus on oncology.
-The program is at a dead stop if insufficiently staffed with people who cannot I-29 integrate and translate the discoveries in gene-disease relationships; -There are three drivers of progress [and resource requirements]: -Sequencing at scale in huge populations; -Huge data input; -Environment that fosters unprecedented collaboration. -Culture of collaboration in genomics seems to be more collegial than traditional academic research; -Traditionalists stand out in a negative way.
-The most noteworthy change is in the people needed to do the work; I-28 -Requirements go well beyond bench scientists; -Challenge is having good IT people, infotech processes and programs to handle the data.
-Have an entire floor of people doing bioinformatics research I-52 -Bioinformatics is split into research and clinical to allow for differences and disclosure limitations; lack of integration becomes a cost factor; -Must move into partnering because it is difficult to hire enough human resources; -But, partner with whom? What aspects of operation do we retain? I-40 -Community hospitals do not have geneticists—these are academic positions; Page 389 | 477
-Geneticists need significant infrastructural back-up with labs, IT, etc. -Nurses play a major role in the coordination of care and follow-up. I-20, 50 -[Institution] is not a university and does not have a computer science department; -Dependent on hiring from academe; -Nature of precision medicine is totally interdisciplinary challenging traditional organizational structures and resources. I-44
-Precision medicine program encompasses over 500 individuals of which 350 are dedicated; -The institution makes an annual allocation; -Funds are allocated from clinical practices and research areas; -Corresponds to three legs: research, education, and clinical practice; -Benefactors also provide funds but generally to restricted areas; -Have also invested in small to mid-sized companies through the business development function when interests align between the companies and a clinical or research program. -Staff development strategy is based on up-skilling and the overall nature of administrative functions is changing rapidly; -For the precision medicine program staff needs to deal with ambiguity because things either do not follow plans or plans are tentative; -Administrative staff must develop deep clinical systems knowledge; many people in the administrative roles have scientific or clinical backgrounds; -Bioethics is also often at the table when a consensus is needed in the face of a new situation; -There are no institutional precedents on which to base a program so the path is created; -Team recently went through a ten-month Drive Leadership Program that emphasized leadership attributes of the future: -Courage to change Page 390 | 477
-Cultivating a sense of urgency -Bold forward thinking -Executive presence -Relational building -Trust development 13 - on-going -Precision medicine has been interwoven with the focus on patient centricity; I-1 scientific and -The field migrates into other clinical verticals. clinical research objectives -The [screening] Program has been beneficial for our patients especially due to I-3 the stability of our patient population. -With [company] are developing genomic risk scores – each variant may not specifically make a patient prone to, say, heart disease but in the aggregate there is a risk; -[Screening] Program enables early intervention or prevention; -Precision tumor typing is the means of moving beyond “bleach, butcher and burn” in oncology; -The institution’s long standing HER, for example, allows the differentiation of natural history and complications of, say, Type II diabetes; -Diabetes may be further stratified under precision medicine; -Lipid group specialists believe that genomic risk scores, not just the mono- variants for familial hypercholesterolemia, will enable a cure for coronary artery disease.
-Precision genomic research is human subjects and requires IRB review and approval; IRBs are becoming more sophisticated; I-14 -Not yet doing interventional genomic trials – these are uncommon; -At [institution] the culture does not have much interest in prospective data gathering or surveys; -Physicians would rather hear: “This is what we found.”
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-Leadership believes that to get needed evidence the precision medicine team must be inserted into the clinic to monitor more closely outcomes and measures of changes; -The [Institution] Gene Technology Center is heavily focused on oncology. We have a close collaboration where they transfer technical expertise to us for purposes of translating to clinical utility. -Like academia, we look to publish but the emphasis is on real-world solutions to problems; the Stanford relationship strengthens that; -[Company] collaboration is to compare some of their original findings to a different population, be it gene mutations or predictive biomarkers; -[Company] is owned by [company] which is the source of the funding; -Collaboration is targeting 500,000 patients over the next five years for whole genome sequencing; -Samples are shared with [company]; -They will return phenotype information with us to be combined with clinical data; -Enables identification of potential drug targets, elucidates disease mechanisms and monitors outcomes; -Facilitates new clinical trials seeking outcomes based on phenotype information; -Allows [institution] to do population genomics. -Are competing with the private sector for talent. -Synapse digital platform for data sharing collapsed under the weight of data sharing and intellectual property conflicts. I-17
-Most oncology patients cannot wait for the results and approvals emanating from randomized clinical trials (RCTs); -Precision medicine clinical trials are few and far between so evidence suffers; -RCTs are absolutely necessary but in a setting where there is confidence and you can have the n that you need. I-15, 16
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-Currently in the process of generating data in pharmacogenetics for behavioral medicine, primary care and Neonatal Intensive Care Unit patients; -Generating data from germline testing; -[Gene] project will capture one in four adults in [state] which is essentially mapping the entire population statistically. -Took four years to generate good results in oncology; -Then one year to expand to all 14 clinical verticals; -Then six months to say let us map everyone; -Now in the process of coming up from behind and generating data and I-51 monitoring and reporting the outcomes with the physicians.
-This group is entirely research oriented and not a Clinical Laboratory Improvements Amendments (CLIA) facility; -CLIA status limits innovation; -With resources can avoid needing to be CLIA to generate revenue; -The Genome Analysis Core develops high output instruments that allow us to sequence fairly large numbers of pulled genomes or exomes and transcriptomes. -Focus has been on new technologies to increase sensitivity, speed, and accuracy. -Now moving into single cell sequencing; -Techniques will lead to more complete analysis, i.e., long read whole genomes; -Moves the needle on current standards to enable more complete analysis so that the prevailing disease solve rate increases from 30%. -Current limitations are a function of both sequencing technology and the I-34, 46 ability to interpret the bioinformatics for clinical adoptability; -The solve rate has not been cracked over the last 10 years; -Current measures are on simple things, e.g., number of sequences done; -Quality metrics matter: turnaround time, costs and charges, etc. -The bottleneck is bioinformatics. Page 393 | 477
I-32 -Interest in genomic visualization started 15 years ago with the first publications; - A genomic visualization contains one or multiple coordinate systems applying a specific layout, partition, abstraction and arrangement (in case of multiple axes) of sequence coordinates. -Feature sets are encoded as tracks and placed on the coordinate systems I-29 allowing enhanced interpretations.
-Current focus is on breast cancer biomarkers; -Across all therapies, how can we better tailor therapy? -Detection currently looking at anything that can be found in blood; I-28 -The difficulty is with circulating tumor cells and cell free DNA is the lack of demonstrated clinical utility.
-Technology is now bringing resolution to hundreds of bases; -Currently investing in RNA sequencing in order to account for pathogenic variants in a gene; -I-30, 33 -This is basic research but with translational implications.
-Currently assessing performance characteristics of whatever things, we are testing; I-26, 36 -If it looks like it could be useful in the clinic, we transfer the test over to the Department of Laboratory Medicine and Pathology which then starts the I-31 official verification/validation of that assay – not a typical path for FDA approval.
-Have an initiative for developing the therapeutic purposes of the genomics under study; -Front end: getting patients to have genetic testing and having genomic I-52 information to inform. Page 394 | 477
-10K program results are ready to be disclosed; this will impact next steps.
-We do not have enough information to inform clinical decision making yet, so it is now a lot of biobanking and predictive biomarkers with the expectation of reaching a point of identifying durable responders. -CAR-T will get individualized based on sequencing; -Significant interest in use of telemedicine for monitoring response and I-40 progress.
-Should other testing alert us to getting genomics testing? I-20, 50 -Data can be pulled from five places in EPIC (HER system) but most is in PDF form; -One goal is to determine what can be done with massive amounts of data already in hand and merging it with genomics data despite the fact that the data is not clean. -But in the aggregate the amount of information that can be married with genomics is staggering.
-One area of focus is on biochemical disorders and finding related biomarkers; -Also seeking to predict whether a tumor would be indolent versus aggressive.
-Much of what remains to be determines will apply broadly to genomics; -Pharmacogenomics brought single nucleotide polymorphisms (SNPs) to the bedside for the largest number of people but we now know that what is reported is simple; -SNPs are locations within the human genome where the type of nucleotide present (A,T,G, or C) can differ between individuals. SNPs are the most common type of genetic variation found among people;
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-Now focused on that part of the genome that is not encoded in coding the protein. 16 - education efforts -Focus groups with patients on biobanking and use of results, i.e., non-clinical I-2 and promulgation actionability and surprised patients; of the program -In 2013 changed protocol so that selected positive results were reported; internally and to -There were concerns on both sides about reaction to the information, but this is patients managed through counseling and follow-up. -NIH grant to study patients’ reaction to genetic results, as well as family reaction when further reported. -Population studies reveal things that were not tested for unless there was clinical cause. -Physician attitude following patient acceptance of testing is “just do it.” -Physicians will find testing valuable at the rate of one at a time—a cascade effect is not likely. -For some patients, genetic information is transformative—they might understand that they have a medical condition that underlies their life constraints. The test results make sense and connect all their life and health experiences. I-5 -Genetic codes are alphabets and numbers—unfamiliar and disjointed. With other diagnoses, physicians read a report in its entirety and see a number. How does a physician get comfortable with precision medicine when the reports are huge and there is no number at the end of the report? -Genetic counselors play a critical role but need automated information in the HER. -Physicians need further guidance on actionability of reports. -Managing patients requires patient engagement with the information. -We are beginning to understand how changes in one’s genetic make-up influence or prediction of disease, but we are a long way off. We are in a long learning process. -Precision medicine’s value is in combination with other diagnostic tools. Page 396 | 477
-Precision medicine principles are being incorporated into medical school curricula and the students sometimes see reports during rotations. I-8 -Physicians do not want to discover a patient’s illness but value a positive result when they can take action. -We devote much time reeducating our front-line docs on what to do with a positive result. I-1 -Role of trust is high in getting consent for [screening] Program participation; -The consent process is detailed and not blindly done; -Ethical analysis surrounding the reporting of selected results in the face of a patient’s desire for information. -Patients are routinely grateful about the findings. I-7 -The idea that we need access to everything is imbedded in the program; -When using a molecular targeted therapy, they realize that we have shot the bolt; -They can say, “This is the way it’s going to play out.” I-3
-In [this region] patients are well-informed and looking for preventative approaches. -Students are more involved in research. I-12 -After training for years in standards for stage four lung cancer, but new actors emerge, EGFR on PD-L1, it makes the physicians uncomfortable. -It took a while for docs to break the habit of prescribing based on anecdotal observations or past experience. -Phase 3 trials have not been around that long for comparison of treatments; -For physicians to operate on these guidelines was a big movement; -There is a burden on medical schools to incorporate information management as a foundation. Page 397 | 477
-Precision medicine requires commitment to life-long learning. I-17 -Patients are variable as never before; -The physician relationship with patients has moved away from one-way; -Patients prepare themselves with social media and internet research, as well as patient support groups; -Awareness of immunotherapy and DNA testing is high; -Patients are engaged in their own care as never before; -Oncologists have need to catch-up to the possibilities. I-15, 16 -Pharmacogenomics for antidepressant dosing caught on fast. -Tumor Board communication is necessary but effective. -We are committed to this paradigm shift. -The future is molecular medicine, but our own past prohibits embracing it. -Emerging markets [developing countries] have an opportunity to leapfrog over 30 years. I-10
-We are in the process of determining the key pieces of education and clinical support; -The focus is on decision support through task forces or committees. -The emphasis is on preparing pharmacists to support physicians; -Also built electronic and computer decision support alerts. -Time demands on physicians limit contact time. -Education of Pas and nurse practitioners is important; -Growing emphasis on certificate programs and mini-courses. I-11
-For physicians, outcome improvements reported at conferences are most effective; -Results circulate actively within [our institution]; -Molecular Tumor Board meetings are open to physicians who order testing; -Monthly seminar series are broadcast widely; Page 398 | 477
-Wide opportunities for education naturally support local efforts. I-32
-Early adopters order things and bring patients along. I-30, 33
-Nurse education is on the front end of the process so that can respond accordingly. -Physician education is on the back end with the report interpretation: -Assist with variants -Clinical actionability -Additional testing -Roadshows are focused on results of patients with rare and undiagnosed diseases; -The geneticists are cautionary as well because traditionally they were not part I-27, 37 of treatment planning.
-Calibrating knowledge needs of pharmacists required observation and I-38 planning for what was needed from them; -Had to learn nature of tests and the applicability.
The three facets of precision medicine are education awareness and empowerment: -Educate on the role of the genome; I-23, 47, -Awareness of the options; 35 -Empower take action on the options.
-Precision medicine education uses all media approaches; -Full-fledged annual conference is a major component of education; -All centers within precision medicine have a medical director; -Program directors frequently have research experience; -Must manage the exploratory culture; -Significant preparatory input on what people feel they need and want; Page 399 | 477
-Resistance derived from incomplete science is difficult to overcome; -Teaching does not necessarily mean that you know curriculum development; -Precision medicine is still an ambiguous term; offering and taking a course alone does not fully satisfy the needs; -Relied on heavy use of focus groups to revamp education; -Patient education is a separate challenge: -Social media; -Point of care education; -Work with existing patient education platforms in place. -Also recognized the need to emphasize pharmacist training; -Nursing education: “once the doctor leaves the room, who is left to answer patient questions?” -The cool new thing has elements that appeal to every level of the care team— attract interest on that basis. 20 -ethical -The obligation to patients is to figure out what we are doing first before we tell I-23 considerations people about it. This is a field where promise gets out in front of actual historically and practice. That is a cautionary tale. currently -The role of bioethics was not present at the birth of the program but became part of the support structure; I-24 -Precision medicine had to have relevance and value for medical practice and this was the basis of translational programs at first then the infrastructural programs that included the microbiome, bioethics, and education.
-Bioethics is also often at the table when a consensus is needed in the face of a new situation. I-44
-In the early days of precision medicine, the focus of ethical discussion was the potential of genetic discrimination; I-42 -Concern in the ethics community was protecting positively tested people from discrimination for jobs, insurance, and other matters; Page 400 | 477
-Concern was the discovery and characterization of targeted rare disease; -Greater possibility of patients being singled out; -Patients chose to forego testing; -Genetic Information Nondiscrimination Act was passed. -Concern expanded to bringing the public to a point of knowledge where they could make informed consent; -Similar concerns about the misinformation associated with the benefits of genetic information and prognostic capacity for success in life or prediction of rare disease; -Public engagement was concerned with correcting misunderstanding; -Additional early conversations around the impact of what positive tests could mean for family relationships regarding parenting, inherited disease, or mutations. -Special challenges in genetics are that tests reveal uncertainties that then require more tests. -In parallel to the evolution of discussions around genetics was the evolution of the field of genetics itself, especially in the interpretation of individual gene function and genes in concert in disease progression; -Emphasis shifted to how knowledge is translated into medical interventions with the goal of mitigating the potential harm in the service of science; -The goal is on balancing benefits in parallel to the risks. -The privacy apparatus in place now is robust and in combination with clinical structure decreases risk significantly; -Contemporary shift to promoting responsibly advances and how to give access to individuals who might benefit. -Prevailing themes relate to fairness and justice. -Concerns flipped from avoiding harm while at the same time pursuing benefit to now promoting benefit while managing potential harm. -In medical practice, genetics is largely done in large academic health centers where there is a level of sophistication and comfort; -The majority of physicians do not have this exposure. Page 401 | 477
-There is a gap emerging between academic medicine and the general medical community – the pattern is to referral for tertiary and quaternary care; -This is not the right environment in which to promote protective health; -It is better to do screening in a primary or community care setting with selective referral to academic health centers to deal with complex issues; -Field must move towards increasing the comfort level of community physicians who can triage the patients as needed; -Interpretation of genetic testing could then be done collaboratively. -Other issues in ethics concern the following: -Scalability of delivery of genomic services; -Capacity creation and expansion; -Technology has reduced testing costs but management of data and associated decision making is the obstacle. -Almost the entire population has genetic predisposition to some disease notable enough to warrant discussion and possible intervention. -Critical question: “How do you scale preventive support structures in response to the fact that we’re all going to be at risk for something?” -How are the obligations to patients who have been tested as patients move from system to system – provider to provider – over the course of life? -In that regard, who owns the data?
-At this point, the focus of ethical analysis is shifting to a systemic level at which we are thinking about how to integrate information into systems that will trigger action when relevant to a patient at a particular moment or upon presentation of a clinical factor or diagnostic test result.
-The center of the mission is aligning the interest of patients and their motivations with available clinical options: -What do patients expect; -What are their hopes? -What are the potential misunderstandings? Page 402 | 477
-Increasing consumer genetic testing has increased the level of patient sophistication; -There are still concerns about insurability or career mobility; -Challenge is alignment of what patients think they will get with what physicians believe they can offer.
-Educational programs must be supported with empirical ethics research. -Must continuously assess patient concerns along the dimensions of: -Paternity; -Family relationships; -Impact of a pharmacogenomic test on Rx availability if it runs against FDA policy or clinical contraindication; -Impact of a cost of a drug.
-Ethical studies can be designed to inform the patient education process.
-Ethics must be part of a team that is building an effective, compassionate machine; it is not a watchdog on the construction and operation of the machine; -Build the most effective delivery model based on patient experience – collaborative in spirit.
21 -evolution and -The reporting of ambiguous results to patients is unacceptable when genetic I-38 issues around testing might reveal the nature of the problem. process flow -In two-thirds of many cases in hematology are said to be idiopathic when there is an explanation. -Must know what to interrogate, how to interrogate, how deep to go. It is not just about finding a cause; it is about determining best management.
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4 - the degree of -Focus has been on sequencing healthy individuals to find out if and when I-2 penetration of PM genetic information allows earlier detection or prevention of disease. into integrated -Seeking transformation of research data to clinical data. practice in -In the pilot stage but can say, “Even though we are doing this for research oncology and purposes, we’re going to discover new genetic contribution to disease. We are other fields of going to find people who are currently healthy but have a mutation in BRCA-1 medicine or -2 gene that puts them at risk for breast or ovarian cancer, or prostate cancer. -In other common areas, e.g., cardiology, we are developing high-risk genetics clinics and are identifying specialists who want to become genetic experts in C-2) Is it a cause their area. or a consequence -Emerging interest in pediatric neuropsychiatric disorders. of some other category? -With time we will certainly find that precision medicine will play an important I-5 role across medicine, but it will be adjunctive to prevailing knowledge.
-I have had a dozen patients where we have found variants that put them at risk I-1 for cardiomyopathy and arrythmia syndromes. -Even in older patients, variants suggest testing their offspring. -Clinicians resist because of: 1. Responsibility for the information; 2. Who will manage and share the information; 3. Lack of expertise on some mutations; 4. Concern about how the patient will view the information; 5. Does it jeopardize my patient’s insurability? 6. Emotional upset for patient and family; 7. Fear of impact on workflow. -There is some over-expectation that precision medicine will become algorithmic; -It will be helpful but it is deeply human and cognitive based – everyone is different: 1. What are they willing to accept in terms of therapy? Page 404 | 477
2. What are their personal views? 3. How does uniqueness fit into to care dynamic? 4. Precision medicine is a guide, but it cannot usurp the art of medicine. I-12 -We do not recruit overly big egos; narcissistic personalities do not thrive. -Collaborative team approach to hiring. -Significant interaction on hiring. -Joint activity on process and improvement projects. -When a physician champions a new way of doing things, they own the process. -Strive to standardize across the system. -Institution’s culture and reputation are for willingness to change. -Culture permits physicians to tell patients that they do not know; -Patients these days do not want dogmatism. I-17
-For example, with EGFR in lung cancer patients we are beginning to see a critical mass of activity. -We are careful in the use of the term precision medicine; -We are engaging these new tools but we do not have the clinical trial that says this drug and this breast cancer will react favorably. I-15, 16
-Focus is on hitting singles; -Given the structure of our institution, migration of the precision medicine program from one group to another was often like starting over. -In behavioral and primary care medicine, the older primary care physicians became our champions; -Constantly evangelizing using physicians with the best experiences in precision medicine guided care for their patients, especially when they have answers to difficult problems where there was no answer before. -Must avoid the problem of physicians feeling dumb in the face of a report;
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-It took three to four years to generate positive outcomes but once a level of confidence was reached: Let’s elevate this to a system-level initiative where the leaders are reporting to the executive leadership team that we’re expanding to I-10 all medical verticals – all 14 clinical programs. The leap took only six months. -The logical next step was to sequence everyone.
-Very few oncology-trained pharmacogenomic specialists; -Baseline knowledge of pharmacogenomics is not very good. -Medical school curricula are lagging; -Most physicians are not working in a tertiary care setting. -Even at large, academic centers, there is a reliance on the outsourcing of I-11 genetic tests which is a huge barrier in terms of locating and keeping test information and having it available and relevant when needed.
-Cardiovascular applications are getting a lot of attention. -Molecular diagnostics in epilepsy and nephrology are under intense study. -A challenge is the build versus buy decision on diagnostic capacity. -Precision medicine was born with cancer but is moving on. -Pace towards universal sequencing is uncertain; -Standards of care do exist in medicine but the market remains a factor; -Patients are demanding information based on 23 and Me and Ancestry.com reports. I-51 -Point of care diagnostics will emerge quickly but not necessarily solely in hospitals.
-Despite the advances, there are opponents internally and externally who say I-39 that genomics has had its day and did not live up to promises. It is time to move on and look at the integration with other omics.
-There is a preconceived notion of the value of genomic testing.
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-The bigger problem is transforming health care to a model where not every piece of care provided is charged for but there is a dilemma—genetic counselors can only charge when there is a positive result even though they are I-32 active with every test. -In precision medicine, more providers will be engaged but this cannot be justified on the basis of revenue. I-30
-Although tests can be ordered and results provided, are they appropriately interpreted?
-Genetic testing is advancing in heart failure; -Some cardiologists want genetic testing more integrated into practice; -Their nurses are being trained in the principles. -The precision medicine cascade has taken this sequence: 1. What is the impact of offering testing to all patients with cancer irrespective of age or family history? 2. Why not offer to everywhere to advance the role of predictive genomics? -As exome cost has dropped testing is used more widely. -Objective to test 100,000 patients for hereditary breast and ovarian cancer, Lynch Syndrome, and familial hypercholesterolemia. -Field is moving towards predictive genomics through annual pilots that has allowed the accumulation of data; -Have accumulated insight on action to take following the positive or negative results in cancer; -Trending in the same direction in other clinical areas. -Still a challenge for feeding data back into the system; -Objective may be a turnkey solution wherein the physician knows enough genetics to order the testing and receives comprehensive guidance for clinical action based on the results. I- -Education is as often demanded as it is pushed. 27,37,47 Page 407 | 477
I-23, 26, -One driver of education is preparing physicians to order tests in certain 33, 36 specific scenarios; -Another is when patients have actionable pharmacogenomic results as well. -Must find a balance between needs and fatigue. -Provide physicians with the whole picture for looking at associated genetic risks and benefits. I-40 -Started in earnest in 2014 for children with undiagnosed disease where we would order whole exome sequencing, i.e., the 2% of genes that code for proteins; -Received an answer only one-third of the time under the best of circumstances. -Sources: -Outside referrals of patients with unknown conditions; -90% of people referred into genetics have symptoms or problems, e.g., children with cognitive disabilities or organ abnormalities; the other are adults with a spectrum of symptoms that cannot be parsed into a clear disease entity; -Patients with a clinical diagnosis of a potential genetic condition sent to determine an appropriate genetic test – either targeted or broad. -Once referred patients are diagnosed, they are returned to the referring provider for care, e.g., lysosomal storage disorders; -Goal is to gather children with rare diagnoses and try to manage with diet and prevention of intercurrent illness.
-Psychiatry does not like pharmacogenomics because it does not explain I-20, 50 everything. It might reduce side-effects or the number of hospitalizations. -Single nucleotide polymorphisms (SNPs) are immutable in genomic analysis. Many other omics are under study, but these are expensive, transitory and move around the genome.
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-The next iteration of the genomic algorithm will be analysis of a thousand SNPs which will enable prediction with 95 % accuracy whether an anti- depressive is going to work. I-44 -The challenge is responding to physicians who say about precision medicine: “This is hard. How am I going to understand this? You need to make it easy.” -The response requires a cadre of providers, a genomics operation support team to help integrate into practice.
-Attempt was made to bring education to the public with the institution’s gene I-43 guide but it was not what the market wanted; -For public policy must contribute to education on Capitol Hill. -For precision medicine to be democratized it must be covered and affordable on a larger scale. -Outreach to affiliated hospitals with education is also essential.
-System must allow even esoteric explorations. I-38 -The present capability is a segue to early intervention trials. -Experience strongly suggests that an algorithm approach supersedes any clinical acumen.
-Current efforts are building for the future. We are still one generation of physicians and researchers away from really seeing precision medicine move forward. The challenges are: -Logistical reasons; -Integration of HER; -Determination of the right testing a priori; -Establishing the right coverage. -But there is also just the lack of science.
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5 - the degree of -Could be further ahead in the clinical use of tumor sequencing to guide cancer I-2 physician buy-in treatment. according to -Do physicians have too much unjustified variability in patient-care decision specialty making? -A positive result from genomic testing can persuade clinicians of the relevance of research. -Hand-offs of patients with biomarkers for a disease is making its way into the system. -Must actively seek clinical champions who want to become the expert working with geneticists and counselors.
-Employment and incentive structures allows physicians to make decisions without an economic consideration. I-5 -Genetic and research aspects are being integrated quickly into everyday medicine. -Patients referred for genetic testing remain the patient of the referring physician but improves physician to physician relationships because there is a powerful tool to discuss. -Will not get 100 % buy-in at first but as patients benefit over time, a standard of practice will emerge.
-Patients with complex histories can often be provided better coordinated care once genetic markers are known. I-8 -Genomics allows a preventative response: -What do you want to do? -How do you want to diagnose? -How do you want to monitor and follow it? -Where are the resources that you have? -How do we couple with HER? -As a group practice we benefit from sharing in the information. -If the only factor were getting a positive result, the process would have failed. Page 410 | 477
-The critical component is what gets communicated and how it is taught to provider and patient.
-Wide scale screening has identified more than a dozen patients with genetic markers. I-1 -Need protocols as to who communicates with patients and when. -Protocols for supporting physicians when a discovery is made are essential. -Internal systems must support decision making whereas a 23 and Me report does not; systems must trigger automatic genetics consultation. -Philosophical foundation of skepticism: “You can apply standards of practice all you want but every patient is different, and I have to be the arbiter of that.” -Intervention for cardiomyopathy, for example, is highly individualized.
-There is a constant battle in medicine between the egalitarian administration and the libertarian physicians, i.e., treating the individual. I-3
-We started by looking to make a definitive impact in the way cancer was seen and treated. -We are still in the early stages of operationalizing precision medicine. -A challenge is telling physicians at the top of their game to do things differently. -Patients today bring information that, one, physicians might not know about and, two, they might use to challenge the physician. -Patient centricity is forcing a collaborative environment. -There is much more of a team approach to care.
-If a physician is doubtful, or if what is proposed interrupts practice patterns too much, or if it creates financial hardship for the patient, then it is less of a I-14 consideration – precision medicine can be a factor throughout. -In the face of positive results, search for the most cost-effective interpretation.
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-Created a collegial approach for such interpretation and allows for recommending approaches. -Litmus test: “What would we recommend if this was our patient?” -Physicians can follow or not. If there was a change was it actually due to the testing? -Necessary to track tumor sequencing based on the decisions for treatment.
-Physicians may not realize that they are practicing precision medicine if it is I-17 well integrated into the system. -Sometimes testing spurs a question: “I have this interesting side effect of this immunotherapy. What would you do in this situation.?” -There is a concern that precision medicine is outdistancing evidence? -There is interest in pushing hard and expanding into other genes.
-Once we said that we were ready to move beyond the pilot location, all parts I-15, 16 of our system were on board. -Changing physician behavior is the hardest thing in medicine. They are trained in a certain way and overcoming dogma is almost impossible. And overcoming institutional inertia is equally difficult. -That said, physicians can welcome thinking out of the box approaches. -A primary care physician with a positive test on which they can act becomes an advocate. -Behavioral medicine is similar but the younger physicians have resisted. -NICU and PICU are using rapid whole genome sequencing for non-thriving infants and children; here the younger physicians are the champions. -On the whole, cannot predict champions. -Specialists follow specialist thought leaders; there are champions in each discipline. -Reaction to a report on a positive finding: “I don’t know what the next 17 pages mean but I know this box at the very top is a summary from a respected
Page 412 | 477 group of live humans. I understand the summary. I feel comfortable in implementing this. I feel empowered.” 1-10 -Sometimes providers longer out of training are less comfortable. -Short duration of consultation time with patients is an inherent problem. I-11 -The employment model helps to incentivize to adopt. -All physicians are using our services in some way or another but influencing the system as a whole is more difficult. -At the start of the program, there was no reimbursement, so this endeavor was an institutional investment; at start approximately $30 million in equipment, capital, and people. -Physicians hate when patients receive bills; expense of precision medicine is an obstacle for many physicians.
-Physicians carry a lot of intellectual goodness but also a lot of baggage. I-22, 48 -There are proceduralist and non-proceduralist specialties with different economics which effects decision making.
-On the scientific side the resistance revolves around financial resources to I-51 support research and priorities; on the clinical side resistance derives from the quality and confidence of data. -The non-true believers in precision medicine continue to crank through the patients. -Even in pathology there are true believers and traditionalists. - “It’s a difficult transition because people have been working for a long time under a paradigm in hand. Deciding to change that opens up to litigation and derision.”
-Heavy lifting had to be done in the lab and by the counselors to make the I-39 process informative. Page 413 | 477
-Significant resistance from urologic oncology. For men positive for BRCA, the choice will still be a prostatectomy. The tendency is to not order the test, but results can have implications for chemotherapy and there are implications for sisters and daughters.
-Disease specific or agnostic – there are challenges across sub-specialties. I-32 -Culture encourages cross-pollination. -Early adopters sometimes adopt before they have a full understanding. - “We have the ability to get so much information about the biological basis of any disease; it’s not just oncology. But what do we do with it? What does it actually mean? Is it clinically significant? Should we act on it? Should we not? So that’s the conundrum we are in now.”
-There is a dichotomy in precision medicine that is a constant tension: I-28 -As a clinician I want to know everything you know based on the sample interpretation. -But, only tell me things that are important for my patient. -Physicians often propose testing ideas: some for fast tracking; other for incubation; still others are expansion of an existing testing capacity.
-Interpretation of genetic testing is full of nuances and must move to a place I-30, 33 where it is less nuanced. Physicians know the diseases they treat and what to do. New information must be value-added.
-Measure precisely then act on it. I-27, 37
-Precision medicine is in the process of refining itself. Get it into the clinic and I-26, 33 exposed and make it better. Then make it better than that. It becomes part of normal medicine. There is an adoption curve.
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-Some of the challenges in consumer-initiated genomics is the history of our system and relationships with patients; it is difficult for the physicians not to be in the driver’s seat of knowledge. I-50 -Physicians are on a quest for certainty but there is never certainty in medicine. -Precision medicine does not change that entirely. I-44 -Success at the highest level has been on the diagnostic front. -Diagnostic systems are solving 30% of unknown infant cases. -We mine the rest and get another 10%. I-43 -One of the big criticisms of precision medicine is that it is not touching the big problems beyond rare diseases; -To satisfy this concern, polygenic risk scores must be the future. I-38 -Physicians have to have the realization that the one size fits all paradigm of medicine is clearly incorrect. -Precision medicine has brought new concepts into clinical verbiage – a victory in itself. -Physicians may not understand the underlying diagnostic techniques but are mindful of RNA, the transcriptome, epigenome, proteome, metabolome, microbiome, etc. and that it constitutes a paradigm shift. -The key is to have a vision even when the majority discourages the shift on the basis of insufficient patient volume, reimbursement, lab delays, difficulty in validation. -Ultimately, the institution must support each vision. -This program plays the role of getting things done: focus on what you are good at and the resources follow at this institution. I-23
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-There are conscious and unconscious biases – real and imagined – but they have to be acknowledged. The science must be designed so that the biases are part of the decision to proceed. -Staff does not want to learn things of limited utility to patients; -Staff wants to know exactly what is needed, not all the science; the education should enable the staff to know the precision medicine moment. -Team organization and configuration are major features of precision medicine. 10 - costs associated -Costs are still largely absorbed through institutional investment. I-14 with any given -Reimbursement is pursued where it is allowed. protocol -Public policy efforts are directed at coverage and reimbursement. -Precision medicine is evolving and while immediate costs are higher it is still in the process of proving that overall costs of care will decrease. 11 - overall costs of -Importance of convincing the payer arm that the results of testing are I-7 administering a worthwhile; precision -Cost of care per week is lower; medicine program -Total cost of care is higher because patients live twice as long; -Payers accept that outcome.
-Efforts underway to reduce costs of testing and passing savings to patients and I-15, 16 payers; -Particularly important for the non-insured, high deductible plans, or when a test simply is not covered.
-Fundamental decisions around the structure of the program include how I-21 allocations will be made from the operating bodies for patient care; -Research support is directed by the research committee. -Support is allocated for three to five years plans which encourages forward thinking and contingency planning. 2 - clinical -Early recruits were medical geneticists for facilitation of reporting. I-2 infrastructure requirements -Medical Grand Rounds were used to introduce and reinforce possibilities. I-5 Page 416 | 477
-Introduced with large clinical facility scope. I-8 C-3) What are the intervening -Initiated on the basis of outcomes to demonstrate value. I-7 conditions between the -Foundation is a large integrated care system that is patient centric. I-12 causes and -Implement care such that cancer intervention becomes global and consequences? economically more feasible for thousands or millions. -We started to see a kind of paradigm shift with regards to cancer because it is more direct to do genomic sequencing and next-gen sequencing: the normal science was advancing.
-Three divisions in genomics: 1. Clinical genomics lab where through a cap and clean environment we can provide genomic based testing right to providers and patients based on a proprietary data and medical records system; I-14 2. R&D Translational Science Center for development or discovery of new technology, new methodology or new tests, or procedures: translate into clinical settings; 3. Shared Services – Clinical research to feed samples and data to the TSC.
-TherraMap of the Navicon Group provides large diagnostic panels of genes and genetic counselors; -For pharmacogenomics there is a buy versus build tension; I-10 -Arguments for building: timing and size of panel -Have the fourth lab in the country to go through MoIDX and have an LCD Code; -Over the next five years there will be a wider scale of genetic adoption in different clinical service lines.
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-You cannot just present raw results, which is meaningless, but the reports cannot be too direct either; I-51 -If you have this A to T change, then you should necessarily implement this strategy for treatment, but it is more complicated; -There is no quick educational fix. -Need a few people willing to get out ahead of the curve and try to figure out some of the questions about how the information is made more digestible and which parts are really implementable form a clinical perspective – a difficult undertaking. -Budget is essentially designed to identify, promote, and help translate researchers, get stuff into the hands of our clinicians, but also to help differentiate and advance our care to give patients a reason to seek our care. It is incredibly broad, trying to accelerate development of any signal that can be generated from an image, either CT, ultrasound, or pathology. It can be one- or two-dimensional, or three-dimensional. It could be as simple as looking at text analysis on a CT scan through an AI algorithm to identify specific texture characteristics of a lung nodule or classifying it non-invasively.
-Project management is foundational to any program; need methodology and rigor with intensive documentation to prove success. I-41 -First goal was to institute project management and secondly to identify standards based on what project management reports told us.
-Sequence cost drop disrupted the environment in the sense that the HR infrastructure was not yet in place, e.g., only 3000 genetic counselors in the US -Impossible for all cancer patients to see a genetic counselor.
Developed three clinical arms: 4. Advanced cancer diagnostics, 2012 I-29 5. Comprehensive program for patients with suspected Mendelian genetic diseases; included familial exome sequencing for triangulation; Page 418 | 477
6. Preventative interpretation to determine healthy population genetics. -Emphasis on rare and undiagnosed diseases using informatics to assist in interpretation. -Challenge: at outset, system may not be ready for the level of complexity of the testing that was coming and the questions that arose. A bottleneck could emerge in the ability to get to the crux of what data was providing. The reality is that a cadre of individuals who tease out the most information possible is needed to fit between the clinical laboratories and the physicians. -Arrived at investigative testing – not true diagnostic testing because there were patients with an amorphous constellation of rare and unusual phenotypes that did not fit any rubrics. The strategy became to test widely and then determine the variances and meaning.
-[Laboratory] is designed to assess high-risk, high-reward projects. Pathology employs the FDA approved tests. -A large testing menu is necessary for precision medicine. I-28
-Each program within precision medicine must have defined deliverables; -Investments in infrastructure are necessary across the board: infotech and bioinformatics especially which may have to be home grown. I-21 -Early years should be focused on capacity building.
-One of the translational programs focused on the low-hanging fruits, i.e., patients with advanced cancer; patients with undiagnosed rare disease; comprehensive team assessment of tumors; funded through a special program. I-30
-Create clinical service lines for consultation with patients and pharmacists. -Costs must be determined with pre-authorization; -Patients are asking for the testing. I-26
-Must promulgate what genetics can and cannot do to consumers. Page 419 | 477
-Bioinformatics should be customized and modeled for the program; I-25 -Will need classification of functions -Will require high-performance computing clusters I-52 -Processing will have to be standardized
-Insufficient number of people entering medical genetics; -Shortage is especially acute for community hospitals. -One word: pharmacogenomics. I-40 -Precision medicine is set up with five translational programs and seven infrastructural, each with a program director and an operations manager. -Organizational structure is flat; culture is fail-fast. I-50 -Translational programs address: pharmacogenomics, epigenomics, the microbiomes, clinical genetics, and biomarker discovery. -Infrastructure programs are the biorepository, medical genome facility, IT, I-44 bioinformatics, bioethics, education, and administration. -Project management supports all. -Physicians serve as scientific leaders. -Perpetually considering new initiatives. 3 - data and bio- -Biobank recruitment effort was succeeding; the local community has been I-2 bank altruistic in allowing banking of samples and access to health information. infrastructure for -While it is still the case that a significant percentage of our physicians do not precision understand the precision medicine program, there has been a big change. medicine -In a partnership with [a company] we have sequenced 145,000 patients – among the largest cohorts in the world. -Biobank research protocol and the IRB create a firewall between research data and clinical care; clinical data must be generated in a CLIA-certified laboratory; -Findings are not disclosed from research biobanks; -Adopted HER in 1996. -Data includes insurance claims data; Page 420 | 477
-Data assets and warehousing must go beyond available HER systems; ratio of data in HER to proprietary systems is 1:3; -HER was conceived for billing and operational tracking, not research. -Advantage was early capture of aggregated clinical data. -HER is 75% of what is needed for research and innovation but is 25 percent of data volume; everything else is 75 percent of data value but 25 percent of the value. -Universal need in precision medicine for data mining to do genotype, phenotype correlations and other analyses to discover new relationships between genes and diseases or individual variants and disease. I-5 -Notion of interviewing patients while waiting for consultations without interrupting the flow of care. I-8 -Original screening program was slow to take-off because there was not much understanding of the potential for patient care; that changed when there was a positive result. I-7 -All data generated by machines must be captured in a data model; -Data warehousing is built around physician work and physician workflow – it was optimization. -Tool design has not caught up to the tasks at hand. -Not all institutions engaged in precision medicine are necessarily aligned philosophically with the NIH. -Many misunderstandings about the role of diversity in a patient population; a homogeneous population is actually an advantage scientifically. The characteristics of our population base make it medically underserved.
-Data is collected and accrued in real time; do not wait until data is finalized I-15, 16 before thinking about clinical implementation;
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-When we have a coherent data story we publish, present internally and externally, and revisit in small clinical settings. -Discussion with physicians is that genomics and precision medicine are implemented for patients now with the promise that all information will be collected and published and explained in parallel with clinical implementation. -Pharmacogenomics has generated a report displaying 250 drugs, as well as gene interactions or direct gene-drug interactions. -Report is then integrated into the patient’s medical record. I-10
-For new genetic data coming in, must develop systems to store it, retrieve it and interface with it. I-11
-AI will assist with interpretation but will not eliminate the need for an I-22 oncologist.
-A challenge and the next frontier is the incorporation of genomic testing into I-51 other “omics.”
-There can be a tension over financial resources among the different services, I-29 especially those that are capital intensive.
-We happily share data with other institutions if it helps get answers for our patients. -Data may come back to us as more of a turnkey solution because a lot of the information is in the databases; -Exome sequencing will expand the data repositories; resolution of I-28 interpretation could change from mass testing to tissue or cell-specific testing.
-which factors more heavily? Bioinformatics or IT? How will we process all I-21 the data?
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-Infrastructure must be built across the board. -Can biorepositories be moved from research grade to clinical grade with SLPs and procedures? -Biobank data goes back nearly 60 years – there is a great opportunity to go I-26, 33, back in time and provide analytics that were previously impossible to do. 23
-There was early suggestion of relevance to psychiatry. I-25 -Started a consortium in 2011. -Ever present challenge of getting pharmacogenomics into the electronic medical record; not a sales driver for the commercial HER producers. -Vendors need to catch-up with charting; we will be catching up forever until a vendor of knowledge fills that void.
-The [guide] does not automatically deposit itself within the HER. I-52 -When engaged with a patient referred in from the community, how do you integrate that history with the HER – not unique to genomics. -Most providers are faced with legacy systems.
-Biorepositories include “healthy” and diseased; these serve as the controls. I-45, 53
-Research and clinical purposes were cleaved at the origination of biorepositories. -Collection is meant to be a population bank, not a disease bank. -A biobank is not necessarily mandatory to start a precision medicine program. That will depend on the scope of the program. Discovery will require it. -A mission of a biorepository can be to accelerate discovery: the better the collection, the faster discovery is possible.
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17 -obstacles that -The institution’s bonds of trust with its patients meant that withholding I-2 were encountered positive results from research was not acceptable; protocols had to be reviewed in the and revised to allow reporting. development of the precision -Precision medicine is an additional tool to further improve outcomes. An I-5 medicine program obstacle can be when physicians think that they have reached the pinnacle. -Flow of knowledge is continuous—but we daily use technology that did not exist during training.
-Patients are concerned about insurance or emotional impact on family I-1 relationships.
-The pressures of practice and economics are overwhelming and lead to more I-7 of learned helplessness than burnout; -A systematic issue with many country-based initiatives is that return of results are not built into the program.
-Medical schools teaching BS grads cannot have the ability to adapt to I-12 precision medicine at the pace of real progress.
-Precision medicine as practiced at different institutions must be careful that it I-14 is not spread too thinly; niches must be established and recognition of what can be done well is mandatory.
-On a genomics report, the physician can read page 1, but there may be 50 I-32 pages. How do they cull through that? -The education tasks surround preparation of the physician to interpret.
-The initial focus was on sequencing and bioinformatics. I-21, 47 -That created the challenge of recruiting computational biology graduates which this institution does not train. Page 424 | 477
-The precision medicine program developed a business plan early with the emphasis of organizing five translational programs and seven infrastructure programs. -Initial mistakes were extensive but were made to be positive learnings. -Carefully designed projects that were achievable around which people could rally with project management guidance; deliverables were carefully defined, and progress monitored. -Leadership made decisions readily but preferred to be proven long quickly rather than defer decisions; avoided making decisions too late to have an impact. -Mantra: start small – move quickly – make decisions. -Team based culture is an asset: orientation is entrepreneurial and deliverables. 19 -other assorted -Estonia leads national efforts of whole exome sequencing the population of I-7 issues 300,000.
-Oxford group might be the most advanced in developing algorithms of genome I-2 wide association studies (GWAS0 data for polygenic risk scores on common adult diseases.
-Biggest challenge for companies is to organize data in a way that is clean to I-21 the point of interpretability and confidence knowing that it was collected in consistent fashion; phenotype data is innately messy given the nature of health care; pulling that data together cleanly is the next step; -Collaboration with [company] is playing a role; -Goals should include digital pathology in which there are actual tissue images in the data set that can play a role in individualization. -Academic environments are capitalist organizations run by socialists; we are a socialist organization run by capitalists.
-A factor in precision medicine is the great amount of time that it takes to move I-50 something from research that is well validated into clinical acceptance; Page 425 | 477
-A genomic analysis produces more in the lab that the reports can capture; these are limited to a subset endorsed by working groups.
-Still need to reconcile how the providers work with the producers, especially I-43 in-patient education, and marketing.
6 -the relevant - Physicians often did not follow best practice guidelines. Prior to precision I-2 clinical dynamics medicine, our [care] program was notable. for precision -The only markers used in the project are the mutations identified by the medicine to be American College of Medical Genetics as having high penetrance – all of these incorporated into have medical actionability; patient care -A clear functional mutation of BRCA gives a 60 – 80 % chance of breast cancer compared to 12 % risk for an average woman. -Exome sequencing with [company] provides results on neuropsychiatric genetic changes; patients so-revealed on [screening platform] are called in for consultation. C-4) Within what context does this -Intervention is on the basis of disease trajectory. I-5 category -Hot links on the genetic reports go into depth; emerge? Context -Patient consultation time is managed to allow discussion of results with the refers to the patients and the participation of genetic counselors; location of -Physician offers creation of a family tree; events or -Genomic patient conferences provide clarity and engage all whenever incidents possible. pertaining to a phenomenon. -The entire clinic has to “own” the patient – a work in progress. I-8 -Physicians are offered alternative approaches to communicating with their patients with positive reports; -External long-term providers often do not appreciate what [we] provide; -Once we can customize medications, we will be at a new level of care.
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-[Program] has made adoption of precision medicine smoother; I-5 -Creation of capacity to detail new discoveries is essential; -Proposals to create “gene kiosks” raises concerns about physician-patient relationship; -Patient/consumer-based issues include: -Quicker turnaround; -Control over outcomes; -Faster results and turnaround; -Access to clinic, -But they want a relationship built on communication and trust. -There is a growing need for the interpretive role.
-Have introduced the principles of implementation science so that we do not rely on the passive diffusion of knowledge; I-7 -Implementation of precision medicine is also about acculturation and engineering. -The idea that you can go to a CME course or can read journals and somehow keep ahead when there are shifts in pathophysiology are illusory; -This reality is not necessarily a threat but certainly creates a sense of fear: “how am I going to manage in this new paradigm?”
-When treating cancer patients, the physician gets frustrate that once a certain point is reached, there is nothing else to offer; I-12 -Cancer care is also trial and error; responders cannot be predicted but it takes months to find out and must live with side-effects. -For implementation of precision medicine, competition can be used to spur people from their usual practice; -Data can be persuasive and shared among the in-house providers; -Until data is front and center you do not understand if there was an issue or a problem. -Willingness is a prerequisite to change, otherwise it is a waste of time. Page 427 | 477
-Systems evolve in medicine based on someone championing change; -Change is a function of the constant feedback that is given on the way we practice, as well as changing and implementing new processes and new science. -In cancer, the care teams extend to social workers who help patients deal with the stigma of the disease; -There are generalist oncologists and subspecialists – they work in unique ways. -Part of our job in the face of incurable cancer is to palliate or buy quality time which is defined by individuals; -Historically, we have projected our own values on what we think the patient should do. -Another mechanism for patients: 1. Have hope that there is a better or another option; 2. Come to a sense of acceptance that they are done. -Genomics is a factor in driving care decisions at this point in the care continuum: patients can be satisfied when they have turned over all stones and better arrive at a stage of acceptance
-In a large system there are goals and metrics to be met by new initiatives; -Constant search for sharing services and capacities to reduce redundancy, create better resources and create efficiency; -Shared services have been central to the precision medicine program but there I-14 is still a big opportunity to further bring shared services into precision genomics. -The integrated structure of [institution] lends itself to translational science; -The culture would rather risk misrepresentations made from over- communication than missing insights from under-communication; -This contributes to continued learning for employees; -Culture must support and encourage professional growth and engagement.
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-We have not met resistance because leadership greases the machinery; have the culture of a common cause. -It takes effort mentally to get to a point of, “I’m wanting to do precision medicine because I’m confident I can help more patients in this setting, and I’m I-17 not going to wait for a randomized clinical trial while patients are passing away.” -We measure objectively that our patients are living longer with greater quality of life with precision genomics; -There is an increasing appetite in small practices in rural America to order genetic testing; the initial struggle over interpretation is waning. -A key factor in stabilizing medical oncology was to base incentives on quality and access, not upon administering infusions of drugs; -[Institution] figured out how to align physician-incentives to reduce the burden of fee for service and the churning of patients; -Fee for service is antagonistic to precision medicine where the right drug for a patient must be provided regardless of the finances and incentives. -There were administrators going back to the beginning that were willing to support the precision medicine vision and the necessary innovation towards better outcomes. -Remoteness of our facility from headquarters allowed a classic skunkworks; -It is not just the concentration of scientists, expertise, and skill, but sufficient shared vision. -We have expanded into all clinical verticals in our system and are working with verticals leadership to implement precision medicine initiatives. -Have found two kinds of physicians: 1. Innovative and forward thinking, inquisitive; 2. Opposite of that. -To implement, find a champion and build consensus with collegial review boards. -Incorporate a summary or dashboard to highlight the specific drugs of interest with the associated pharmacogenomics; back-up in PDF. Page 429 | 477
-Think more about leapfrogging – the decades of dogma in medicine makes PM adoption slower.
-Foundational pieces of pharmacogenomics are underway; seeking ways to incorporate discrete results into the HER.
-Precision medicine can give precise information about the biological state of I-10 the patient, e.g., microbiome data can indicate response to immunotherapy.
-Collaboration with other bioinformatics groups and the Broad Institute I-22, combines our patients with their analytics; 48 -Goal is to provide tools that enable fundamental research and make data more amenable to scrutiny. I-51 -Value proposition: without tools provided that establish an internal expertise there will be a tendency to go to the inconsistency of the outside world. -Build the knowledge and technology capacity within.
-Genetics testing provided at no cost to patients once we were able to secure tests for $250; -When patients test positive, relatives are offered tests at no cost; -Family variant testing is supplemented with You Tube education. I-39 -Staffed at this facility with six oncologists but rely on a tele-genetic strategy with counselors from another facility; -Subsidiary hospitals broaden our racial and ethnic population base. -Constantly assessing barriers to care following testing.
-Clinical trials are coordinated by a unit with precision medicine.
-The current traditional pathway is disrupted by precision medicine, but we lay the reporting of the test results and interpretation on the traditional pathway; I-32
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-Created a parallel path for specimens for clinical and research purposes in I-29 order to have a proof principle that could achieve comparable results; -Also learned that there’s diversity in how that data is interpreted in those clinical laboratories and what is returned; -There was also variation in clinical interpretation which became apparent from parallel analysis; -Interpretation challenges emerged in both paths; -Does the result really reflect the condition of my patient? What to the results mean? For example, if it is a single variant in a recessive condition where only one of the alleles is disrupted, what does that mean? -Data is vetted by genetic counselors and then geneticists would make a decision. -The reality is that you need a cadre of individuals – a group expertise that somehow fits between the clinical laboratories and the physicians that were going to tease out the information. -Dissimilar from early genetic testing where it was a single gene with an established etiology; -Evolved to investigative testing, not specific diagnostic testing, seeking pattern is a surfeit of data for which there is a gap in capability to synthesize the data; -Biostatisticians and bioinformatics specialists worked with clinical investigators to make sense of it. -Groups compelled to come together; -Assembled teams to interpret unsolved cases; -Challenge to fill the chasm so added a third arm for data interpretation: -One-third of the findings are ambiguous at best; one-third nothing; one-third makes sense.
Oncologists fall into three buckets when requesting diagnostic tests: 1. Need for a specific test; 2. Order a disease-specific panel; 3. The biggest test you have. I-28 Page 431 | 477
-Partner with different internal groups to reach the next level of genomics; -Focus on identifying gaps in the diagnostic regimen -Participation with clinical implementation team. I-30, -Results enter the HER and at the prescribing event physicians receive a 33 prompt; -If no results are in the HER, physicians are prompted to order pharmacogenomics. -Coordination is critical – every component of the institutional structure contributes towards the program.
-Emerging question: how do we climb the ladder and encompass health people? -On alert for errant diagnoses: false negatives or positives have greater impact on knowledge accumulation. I-25
-Adapting precision medicine to the multifaceted nature of immunotherapy and CAR-T. -Building synergies among services. I-31 -Created an internal board to take data, re-examine it and look at genetic variants of unknown significance and doing functional studies to get an answer.
-Transition to pharmacogenomics favored clinical pharmacologists not basic I-40 pharmacologists. -An initial mistake was the belief that we have to teach physicians about genomics – not a productive move; I-50 -What we report today tells part of the truth but as a clinician you are always dealing with part of the truth.
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-Science cannot explain yet the vast majority of variants, a role for machine learning and augmented intelligence. -Work is perpetually collaborative. -Results are provided in a usable form; -Have quantified clinical judgement using standardized rating scales; -Has enabled within a brief duration a visible range of improvement.
-Initial struggle was finding labs and lab staff who understood patient care; -Had to enculturate for expectations, urgency, and work-life styles, especially with extended tests; I-38 -Program has taken institutional experts and provided resources and time to extend knowledge of the precision medicine enterprise. 15 -status of -When best practice guidelines are built into clinical decision support tools in I-2 formation of the HER, the default follows the best practice guidelines. precision -Departing from the guidelines is more work than following them; medicine as the -Variability drops – a good discipline for precision medicine. standard of practice -The precision medicine value is in the predictability of response to therapy; I-5 -It provides disease recognition prior to progression and symptoms.
-Precision medicine challenges the way we look at, interpret, and follow I-8 clinical guidelines; -Illuminates the response to medications; -More consistency and customizable to have specific guidance or treatment; -Goal is to customize to get to the best endpoint.
-Use care networks to expand the base of patients among like-minded I-17 institutions for re-examination of clinical guidelines; -Instead of one gene seen in one patient in one institution, can have similar patients in various institutions; Page 433 | 477
-Can compare outcomes and response to drugs; move from an n of one to 20, etc. -Networks or consortiums will become more popular.
-At this moment in time the best possible test is the best possible test but five I-11 years from now that may no longer be the case. If we rush to standardize around, say WGS, and that becomes a standard of practice so much the better. But WGS will be improved and we might be limiting ourselves by boxing it in now.
-From a physician’s point of view, if the standard of care is followed, there is I-22, no blame but, what if the standard successfully treats only 30%? 48 -If I have a method that does massively better in the face of a standard, an adverse effect in the non-responders is seen as fault. -Precision medicine must work in a different system than the current one where it does not work optimally; -The current system does not have the capacity to treat once cancer patient at a time, but it has the time to lose once cancer patient at a time.
-A good percentage of cases where a diagnosis is facilitated as a group through I-29 the activities of enough informatics, genetics, and clinical science to pull information together missing in the clinical report and the clinicians; -The impact of that has highlighted the role of precision medicine; -Challenge is institutionalizing that support. -Also missing in the research path where there is still a gap in linking genetics with clinical observations and planning.
-When clinicians are asked what tests are needed, they rattle off guidelines. I-28 -If ordering the biggest test, they get information they cannot use or need; -Difficult to keep pace with the information.
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-The big idea emanating from a [special] grant was how to make I-26, pharmacogenomics part of a standard of care when not everybody has the 33, 36 testing or patients that need the testing. -Sequenced 11,000 people and release data into practice where there is discussion. -Consulting EPIC for each patient to see if there is a study underway is not yet a standard of practice for clinical pharmacologists. -Standards of care are often driven by inertia; -The information is there for the entire team to open but many have not yet taken that step; -Strategy is to create a confidence that the access is there. If the physician cannot use it, support is available for interpretation and decision that creates a sense of enablement; -Rate studies show that 99% of patients have an actionable result if not now, then in the future; -Getting providers to interact with that information is the critical first step. -Role of the pharmacist as liaison to interpretation and how it means something to a provider is valuable. -The critical moment of adoption for this practice across the rest of the world will be when it is a vended product. -When a knowledge vendor has a product that incorporate this concept to them means something on which the clinician must act.
-Test results must be as direct and interpretable as prevailing chemistry and I-50 other assays.
-Even in rural communities oncologists order tumor genomic profiling. I-43 7 -whether there are -In pharmacogenomics the majority of people have variants in genes that affect I-2 formal clinical drug metabolism rates to help get the right dosages: fast metabolizers need a protocols higher dose. currently in place -We are moving towards regular use. Page 435 | 477
or if protocols are C-5) Is this a work-in- -In primary care, “Okay, what can we do next? How can we make that better? I-8 category a progress How can we standardize this?” contingency - “Why do I have to see every single patient for a return appointment in (having a bearing person? How many of them can I convert over to a telehealth visit and saver on another their time and mine?” category)? In other words, - “It’s far too soon to have clinical guidelines or standards of practice for I-14 what is change in precision medicine. It would actually inhibit practice.” this category dependent upon? -All stage IV patients appropriate for therapy get genomic sequencing. And I-17 This refers even though they may have a standard of care option, whether it be chemo- or usually to immunotherapy, that precision medicine test allows us to explore more unplanned options.” change (Strauss -Tracking is done now. There are clinical protocols that track outcomes. & Corbin, 1990; Retrospectively, we look at what happened to those patients and publish that. Swanson, 1986). -We found that if we map the entire genome of languishing kids, we can make I-15, a diagnosis in about half the cases and change their management. 16 -Diagnosis gives the missing answer to physician and patient families – can then decide on management. -Sometimes they respond other times it is futile.
-There are groups that simply do not believe that there is enough evidence that I-10 pharmacogenetics has any place in clinical care. -Must move to standard clinical trials. -Drug testing in pharmacogenomics is different.
-If we build it, we can commercialize it. I-11 -Attempted a for-profit spin-out which could not be capitalized.
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-Currently do not have as difficult a time to convince oncologists to use genomic medicine or testing because it is becoming a standard of care, especially in Stage IV. -[Drug] and other products support this shift.
-In our large study we learned about how to put genetic testing into the care of I-39 cancer patients proactively in real-time care. -At [facility] every cancer patient is a non-research setting will have genetic testing. -Referral pattern of patients following genetic interpretation: -if negative, patient returns to referring physician; -if positive, management shifts to main facility. -Huge and growing demand for genetic counselors. -Thrust: transform from a research pilot to actual clinical practice; -Volume: 3000 patients cancer patients per year.
-There is a growing desire for precision medicine adoption; I-32 -The implementation of testing into practice is the challenge. -Not yet incorporated into guidelines; -No major studies for clinical utility to say this is the position where tests should be used. -Often a challenge in bridging and returning patients to the referral source. -Conservative physicians expect to stay within guidelines; must have demonstration of clinical utility, but patients are pushing providers to that territory. 8 -the process for -Provide resources to learn abnormalities quickly; I-5 internal protocol -Take it stepwise: sentences to paragraphs to additional material; development and -It is gradually integrated. screening -There is implementation from the lab side: -part of the regular test ordered through HER; -gain insurance company support; Page 437 | 477
-if interpretation is difficult, consult lab colleagues -develops a culture of dialog across services.
-The Clinical Pharmacogenetics Implementation Consortium (CPIC) is I-10 working on three sets of guidelines; -Strong implementation in Canada, UK and Europe, places which do not have insurance discrimination fears.
-To align strategic goals, created a list of metrics that matches goals to metrics. I-41
-Organized learning from mistakes; I-29 -To have a playbook need internal investment; -Access to good laboratories; -Invest in education top to bottom. -Computational team must understand underlying data, the genomics, and translational omics. -There is emphasis on connectivity of systems which is infrastructural as well as scientific. -IT and informatics might seem easy, but the people need education. -Clinical research coordinators play bridging role. -Activities start as quasi-research, then translational; -Manage for purpose of incorporating what is already known. -Objective is to find missing pieces and expertise in which to invest and complete the picture.
-Have had a challenge with CAR-T in standardizing across multiple facilities. I-31 12 -issues with -Provider-payer structure is all one entity; profits from the health plan can I-2 payers for transfer to the provider. reimbursement -Pushback tends to happen with genomics at the start of the process of care; I-8
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-There is also reticence for impact or insurability is passing because people are getting sequenced widely; -Physicians are not pushing back and are becoming advocates with payers.
-Allowing the sequencing for 60 selected genes for a population of patients free I-1 of charge through the health plan to establish a baseline.
-Publication of results in a [peer reviewed] journal helped convince payers; I-7 -That process must be replicated widely; -The article showed that the offset of the much higher pharmaceutical costs was from the dramatic reduction in the end of life hospitalization; -Open question: is that a function of molecular intervention or richer engagement and earlier discussions with patients?
-Our integrated system is better for keeping people healthy. I-3 -That provide a bridge for moving into preventative health care using precision medicine.
-How can we either reduce our costs or improve our testing to provide I-14 competitive advantage? -The emphasis is on learning from physicians why or why not choosing this type of testing.
-Beta has a payer arm so maybe we would have better luck at getting the drug I-15, for patients. 16 -Our payer has been willing to listen to some of what is said, but they also act as an independent payer and challenge our claims. -Most telling statement is that “We don’t want to be an outlier or on the front end of the innovation curve.” -Translation: “We want to cover what other payers are covering and we don’t want to cover what nobody else is covering.” Page 439 | 477
-That reasoning produces a regression to the mean. -Payers are the least innovative aspect of health care because market forces and incentives are misaligned. -Must take a two-pronged approach: 1. Most payers will follow Medicare – approach with Medicare is to provide data and information, creating relationships that inform; 2. Working directly with other payers, including our own, and educating them. -Slow process that often does not feel hopeful. -As important is working diligently and demonstrating reduction of sequencing costs so that we can test even without a payer. -Seeking a level where patients can pay out of pocket – important for high- deductibles and the uninsured.
-History of non-payments is a problem for physicians. They do not want to I-11 intermediate and hate when patients get billed. -Focus is on care, not finances.
-It is as much about the choice of therapy as the diagnostic. I-22, 48
-Bigger problem is transforming away for fee for each service; I-39 -For genetic counselors, they can charge only after the care and only of the patient was positive; -Genetic counselors have to be there but we cannot charge for them reviewing every test result; -The paradox is to bring in more people for an aspect of care that cannot be justified on the basis of revenue. -The argument is weak: “This is the better thing for the patient to drive towards precision treatment, but we can’t always show you you’re going to make money on a one-on-one basis.” -Offsets may occur when routine follow-up is needed based on genetic results. Page 440 | 477
-The social and genetic familial linkages are not yet in the payer’s equation.
-Coverage pace has been incremental and a continuously shifting landscape; I-30, -Possible seen as a slippery slope financially: 33 -start with a few genes -then the exome -getting Medicare to create a code -getting a commercial payer to cover -move ultimately to other omics. -Lobbyists heavily engaged in driving coverage. -Physicians ask: “Is it reimbursed? What’s insurance going to pay?” There is no consistent answer. -Insurers vacillate: -pharmacogenomics was paid last year, but not now; -insurers see some genetic testing and then challenge need for additional genes or exome. -Having more positive conversations with payers who want to send their patients, especially rare diseases which consume huge costs for years before there is a determination of an underlying disease.
-Little resistance to providers to new tests but sometimes with individualized I-27, tests there’s difficulty with payment; 37 -Proteomic tests have a high price tag. -Lag in getting these to proper authorities, an impediment to adoption. -Encourages a culture of evidence in the program: validation, reproducibility, and clinical impact. -Need a fully integrated scientific, legal, and business team to make the case to go from non-reimbursable to reimbursable. -[Another institution] chose not to take this approach and does not develop tests; have chosen to be followers.
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-To lead, must develop the capability to develop the new diagnostic tests that will define precision medicine, whether used narrowly or widely.
-An entirely new model, especially on the therapeutic side of precision I-43 medicine has to evolve for paying now for something that affects a lifetime. 18 -obstacles in the -Physician must make decisions as to what happens or does not happen. I-7 current -Limitations are defined by cognitive capacity around data. development of -Biggest revolution will be around expert systems – computers are the program. outperforming radiologists and pathologists in diagnostics. -The impact of combining computers and clinicians is unknown. -Response to physicians dubious about precision medicine: “Well, if we understand how you do your work, and we understand your workflow, and we understand how you use your HER, we can present this information to you right when you need it so that you can use it to make a better decision about how to cure for the patient.” -EPIC does not have any way to represent genomic data as structured data in the HER. -Without structured data – just a PDF – there is no decision support in genetics; knowledge cannot be integrated and must build one-offs. -This institution is the first EPIC user to implement a genomic indicator module, but it has limitations. -Current operating culture of medicine is an obstacle to precision medicine: physicians must spend time on things not in the best interest of the patient, e.g., documentation, revenue optimization, use of poorly designed systems, capture elements of quality unrelated to true quality. -The essential nature of the conflict: If a cardiologist is told you need to order pharmacogenomic testing of anybody being considered for [specific drug] because 15% of Caucasians cannot convert it into an active ingredient. If you want best care that is a test you need to do. The cardiologist replies, “The evidence is insufficient. There’s ten times more evidence for adjusting the dose based on administering a proton pump inhibitor, which is done regularly.” Page 442 | 477
-Another way of replying: “I’m the professional and this is how I was taught – I make and live with the decisions.” -Or, it is really about: “Leave me alone. I want to practice the way I want to practice.” -Should outcomes be sacrificed to maintain autonomy?
-Originally invited into an NIH genomics consortium but ultimately declined I-2 for lack of participation in the strategic planning.
-We are still at the front-end of a long journey. Currently there are limitations I-12 on what drugs and treatments are actually offered but that will change with better understanding of the genome. -With precision medicine we can move upstream to practice preventable medicine. If 15% of cancer comes from an inherited germline mutation, we are not capturing them. Too many young patients present with metastatic disease that we should be able to know in advance.
-There is a concern at many institutions that precision medicine can snowball to I-10 the point where the institutions will not be able to scale-up adequately to meet the needs and demands. -There are not enough academically prepared people. -Precision medicine is the right thing to do. The best course of action is for collaboration to happen and not have local groups unable to leverage knowledge and experience it across these platforms. -Business development and proprietary nature will have to accommodate. -Differences will have to be adjusted in project implementation. -It is a national conversation. -Need IT portability across platforms and move away from PDF files. -Need alignment in terms of clear genetic variant reports. -They all get different phenotype and genotype results based on the laboratory.
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-Obvious need for greater integration of genomic knowledge and eventually determine where the other omics fit into the picture. -Numbers of patients cared for needs expansion to allow for clinical trial results. -Coverage is still ambiguous and fear of discrimination remains. -Ownership of information and related consent are still in flux.
-Fear of scale requirements and related costs. I-11 -Expanding our franchise has challenges to scope and branding; -Looking at a kind of modular turnkey—hospitals choose what is needed and what they will do. -Does this institution have the ability to evangelize precision medicine and provide support services.
-Rationalizing and selecting from multiple tests doing the same thing; I-32 determining clinical sequencing platforms (internal or commercial) in any given circumstance. -There are differences on different tests; -Reliability is variable; -Big general test versus specific gene tests -Not one size fits all. I-29, -Noise in the system is huge but less so in genome sequencing; 47 -Identifying where changes and variations occur differs with continuous data management versus discrete peaks. -Multiple modes of evidence come into play. -Resolution is so fine from what is playing out in the laboratories; -Down to a single base. -Traditional apparatus and environments are not prepared. -Genetic counselors deal with enough complexity just to stay on top of the gene phenotype associations and the dysmorphology and emergence there; Page 444 | 477
-Have been force-fitting roles which is an obstacle to getting to the level of patient care desired. -Next decade will resolve many issues, define diagnostics, and determine venue for treatment.
-Not limited by the fact that the team cannot sit down and look at cases, but it is I-28 a strain and limits operation to one-off results without basis for comparison. -Clinical labs have to focus on what is in hand; newer tests are experimental, so the institution formed a separate group to develop tests and coordinate with precision medicine on innovative projects. -Effort is closely governed with representatives from clinical stakeholder groups.
-It takes well-trained and well-intentioned physicians many years before I-30, genomic medicine flows seamlessly into practice. 33
-Genomics, and omics testing in general, is part of a strategy for offering out to I-52 others. -Still at a point where such testing is not remunerative. -Companies offering testing subsidize the charges in exchange for data. -critical aspect is a marriage of a rich base of medical records with genomic data; -Challenge is translating to clinical relevance because many physicians are not yet buying the benefits; -Those resisting ask the question, “How am I ever going to incorporate this into my practice given the way medicine is structured? How am I going to have access to all the experts I need at every level to interpret this?” -EHRs not yet equipped for finding genomic data and putting it into a form that makes clinical sense; -Must also conform in time to the episode of care.
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-There are issues of managing storage capacity – inefficient and too costly to do in house. Cloud based is an alternative for scaling. -With respect to data curation in the cloud, do we use [institution’s] pipelines or use what [outside concern] has developed with the Broad Institute. -How would we manage at the lab level with data residing in different places? -The technical gaps are somewhat crushing at points.
-The FDA is still sorting out the boundaries of what can be reported from I-20, testing; 50 -Genetic interpretation is acceptable; -There remain reservations concerning drug recommendations in the genetic reports based on the testing.
C-6) Is there 14 - monitoring and -Best practice guidelines became a driver. I-2 covariance measurement of -The proven care approach was not done systematically for publication, but it between this outcomes did create an ethos for quality that extends to precision medicine. category and -In the case of Type II diabetes treatment, there was a dramatic effect as other categories? measured by decreases in mortality, amputations, ER visits and costs of care. Covariance -This approach effectively reduced physician autonomy and was a good occurs when one cultural preparation for genomic medicine. category changes with the changes -Comparison of physician outcomes – in an anonymous but privately disclosed I-12 in another way – was a valuable way to change practice. category without a causal -The program is still too young to do interventional clinical trials; not engaged I-14 connection in first in human trials. -Even though we are one organization, the sponsors and partners see us as multi-institutional; Page 446 | 477
-An argument can be made that each location within our system has a different understanding even under one protocol; -Working towards consistency across the system; -Follow a value-based care model across the system but still need to do more outcomes research and clinical utility studies to convince payers of test efficacy. -Expansion of technology platform and expertise has led to more discovery research. -Still evolving a consistent process for monitoring patients being tested across the system. -Focus on creating awareness among providers of test availability and ways of ordering; ordering trends are positive for penetration of precision medicine. -There can be spikes in ordering; follow-up needed to determine the response to the structure and content of genetic reports and the clinical value of the information; -Specific metrics: -What were the results? -Are there correlations? -If not followed, why? -What changes were made, and why? -Clinical programs represent different disease areas making the task to identify care process models for consistent use throughout the system. -The leaders of the clinical programs want to know specifically with evidence when the testing occurs and the postulated associated benefits to indicate when testing is recommended, e.g., tumor sequencing has inserted next generation testing for every newly diagnosed stage-four cancer patient. -When the stage is updated, the physician is prompted and can elect to proceed or explain why not. -The care process model, therefore, is still emerging. -Moving similarly for pharmacogenomics testing.
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-Currently creating outcomes data to identify specific patient benefit but still using a shot-gun approach: capturing prescriptions received, returns to clinic, re-admissions, ER visits, re-hospitalizations, and other factors. -The inherent difficulty is that analysis has been retrospective which introduces confounding variables. -Seeking to move to randomized controlled trials (RCTs) where cohorts are in protocol or not; -Attempted RCTs with pharmacogenomics but the Institutional Review Board (IRB) tabled the application; IRBs are catching up with the science here and elsewhere. - “The idea is to keep trying different angles to get to the gold standard approach. For now, it is a retrospective data pull with different endpoints to see what might be in the data. That might drive what a clinical trial might look like in the future that can be controlled.”
-Positive impact of an interim program assessment drove both the I-15, 16 administrative and payer sides towards continuation and expansion of the program; -Regular reporting is part of the annual budgeting process; -Simultaneous to institutional support growth there was a grassroots movement among patients and philanthropists providing support; served as a surrogate for objective outcomes. -It took three years to generate documented objective outcomes beyond the patient-physician experience, community enthusiasm and other intangibles.
-Oversight requires that outcomes are captured – not just clinical or research I-41 outcomes, but outcomes of the overall precision medicine project. -In addition to meeting goals, are asked “What did you learn from this?” -Emphasis on learning from success and failures. -Documentation over the years also includes a series of outcomes, i.e., the number of publications, presentations, policy interventions, abstracts, posters, Page 448 | 477 new articles, placement on boards and committees, and the like as benchmarks for program impact.
-Expectation is for total clarity in the business plan with overseers – the heads I-21 of Research and of Practice – on projects and related deliverables. -Initially success was based on project completion as a surrogate for impact; -By the third year we worked with the leadership to design a formal metrics report meant to be common across the centers; -The design process itself was valuable. -The results earmarked progress and success in allocating dollars to projects that delivered grants, contracts, and publications; -Having more grants and publications in the genomic space was a benchmark of work that could be done regardless. -When able to co-develop technology, partnered with companies on collaborations beneficial to both parties. -Internal program units are compared by tracking metrics unique to each. These include: -patients enrolled in wide-study; -patients seen in pharmacogenomics activity; -samples sequenced for microbiome activity. -Metrics continue to evolve with the growth of the program.
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APPENDIX G GLOSSARY OF SCIENTIFIC AND CLINICAL TERMS
Active pharmaceutical ingredient (API): refers to the biologically active component of a drug product (e.g. tablet, capsule).
Acute lymphoblastic leukemia (ALL): Acute lymphoblastic leukemia is the most common childhood cancer. It occurs when a bone marrow cell develops errors in its DNA.
Agonist: a substance which initiates a physiological response when combined with a receptor.
Antagonist: a substance that interferes with or inhibits the physiological action of another.
Attenuated virus (vaccine): is a vaccine created by reducing the virulence of a pathogen, but still keeping it viable
Biobanks: a type of biorepository that stores biological samples for use in research.
Biomarker: a measurable substance in an organism whose presence is indicative of some phenomenon such as disease, infection, or environmental exposure.
Biorepositories: biological materials repository that collects, processes, stores, and distributes biospecimens to support future scientific investigation
Chimeric Antigen Receptor T-Cell (CAR-T): cells that have been genetically engineered to produce an artificial T-cell receptor for use in immunotherapy.
Companion diagnostics: a diagnostic test used as a companion to a therapeutic drug to determine its applicability to a specific person. Page 450 | 477
Comparative Effectiveness Research (CER): the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, or to improve the delivery of care.
Electronic Health Records (HER): a digital version of a patient’s paper chart.
Epigenetics: genomic modifications that alter gene expression that cannot be attributed to modification of the primary DNA sequence and that are heritable.
Epigenomics: the study of the complete set of epigenetic modifications on the genetic material of a cell, known as the epigenome
Evidenced based medicine: the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.
Genetic sequencing: the process of determining the nucleic acid sequence – the order of nucleotides in DNA.
Genome: the complete set of genes or genetic material present in a cell or organism.
Genomics: the branch of molecular biology concerned with the structure, function, evolution, and mapping of genomes.
Genotype: the genetic constitution of an individual organism.
Germ theory: microorganisms known as pathogens can lead to disease.
HER2: an oncogene that is an important biomarker and target of therapy for approximately 30% of breast cancer patients.
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Human Genome Project: an international scientific research project with the goal of determining the base pairs that make up human DNA, and of identifying and mapping all of the genes of the human genome from both a physical and a functional standpoint.
Individualized medicine: (see Precision medicine)
Interventional radiology: a medical subspecialty that performs various minimally invasive procedures using medical imaging guidance, such as x-ray fluoroscopy, computed tomography, magnetic resonance imaging, or ultrasound.
Killed virus (vaccine): a vaccine consisting of virus particles, bacteria, or other pathogens that have been grown in culture and then lose disease producing capacity.
Large molecule pharmaceutical: a low molecular weight (<>900 Daltons) usually biologic compound that may regulate a biological process.
Lipidomics: the study of the structure and function of the complete set of lipids (the lipidome) produced in a given cell or organism as well as their interactions with other lipids, proteins, and metabolites.
Metabolomics: the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system are known as the metabolome.
Monoclonal antibodies: antibodies that are made by identical immune cells that are all clones of a unique parent cell.
Monogenic diseases: these diseases result from modifications in a single gene occurring in all cells of the body. All human beings have two sets or copies of each gene called “allele”; one copy on each side of the chromosome pair. Monogenic diseases are responsible for a heavy loss of life.
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Next Generation Sequencing (NGS): also known as high-throughput sequencing, is the catch-all term used to describe a number of different modern sequencing technologies. These technologies allow for sequencing of DNA and RNA much more quickly and cheaply than the previously used Sanger sequencing, and as such revolutionized the study of genomics and molecular biology.
Omics: refers to a field of study in biological sciences that ends with -omics, such as genomics, transcriptomics, proteomics, or metabolomics. The ending -ome is used to address the objects of study of such fields, such as the genome, proteome, transcriptome, or metabolome, respectively.
Oncogenes: refers to a gene which in certain circumstances can transform a cell into a tumor cell.
Oncogenesis: refers to the development of a tumor or tumors.
Patient centricity: the process of designing a service or solution around the patient.
Peptides: short chains of between two and fifty amino acids, linked by peptide bonds. Chains of less than ten or fifteen amino acids are called oligopeptides, and include dipeptides, tripeptides, and tetrapeptides. A polypeptide is a longer, continuous, and unbranched peptide chain of up to fifty amino acids.
Percutaneous surgery: any medical procedure or method where access to inner organs or other tissue is done via needle-puncture of the skin, rather than by using an “open” approach where inner organs or tissue are exposed.
Personalized medicine: (see Precision medicine)
Pharmacoeconomics: the scientific discipline that compares the value of one pharmaceutical drug or drug therapy to another.
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Pharmacogenomics: the study of the role of the genome in drug response. Its name reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of an individual affects his/her response to drugs.
Phenotypes: term used in genetics for the composite observable characteristics or traits of an organism. The term covers the organism’s morphology or physical form and structure, its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior.
Polygenic disease: A genetic disorder that is caused by the combined action of more than one gene. Examples of polygenic conditions include hypertension, coronary heart disease, and diabetes.
Polymorphisms: the occurrence of two or more clearly different morphs or forms, also referred to as alternative phenotypes, in the population of a species.
Precision medicine: a medical model that proposes the customization of health care, with medical decisions, treatments, practices, or products being tailored to the individual patient, instead of a one‐drug‐fits‐all model.
Precision pharmaceutical: see Precision Medicine
Proteome: the complete set of proteins expressed by an organism. The term can also be used to describe the assortment of proteins produced at a specific time in a particular cell or tissue type. The proteome is an expression of an organism’s genome.
Proteins: any of a class of nitrogenous organic compounds that consist of large molecules composed of one or more long chains of amino acids and are an essential part of all living organisms, especially as structural components of body tissues such as muscle, hair, collagen, etc., and as enzymes and antibodies.
Proteomics: the study of a proteome.
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Recombinant DNA (rDNA): DNA molecules formed by laboratory methods of genetic recombination (such as molecular cloning) to bring together genetic material from multiple sources, creating sequences that would not otherwise be found in the genome.
RNA transcription: the first of several steps of DNA based gene expression in which a particular segment of DNA is copied into RNA by the enzyme RNA polymerase. Both DNA and RNA are nucleic acids, which use base pairs of nucleotides as a complementary language.
Small molecule pharmaceutical: a low molecular weight (< 900 Daltons) organic compound that may regulate a biological process by binding to a macromolecule
Stem cells: special human cells that are able to develop into many different cell types. This can range from muscle cells to brain cells.
Systems biology: is an approach in biomedical research to understanding the larger picture—be it at the level of the organism, tissue, or cell—by putting its pieces together. It is in stark contrast to decades of reductionist biology, which involves taking the pieces apart.
Therapeutics: a treatment, therapy, or drug.
Transcriptomics: the study of the transcriptome—the complete set of RNA transcripts that are produced by the genome, under specific circumstances or in a specific cell— using high-throughput methods, such as microarray analysis.
Whole Exome Sequencing (WES): a genomic technique for sequencing all of the protein-coding regions of genes in a genome (known as the exome).
Whole Genome Sequencing (WGS): the process of determining the complete sequence of nucleotides in an individual’s DNA. It is also known as WGS, full genome sequencing, complete genome sequencing, or entire genome sequencing. [END OF STUDY]
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